UCLA ENGINEERING HENRY SAMUELI
SCHOOL OF ENGINEERING AND APPLIED SCIENCE
Computer Science
Department
SELF-REVIEW
June
2014
4732 BOELTER HALL LOS ANGELES, CA 90095-1596
Self-Review of the UCLA Computer Science Department
Lead author: Jens Palsberg, Department Chair
June 11, 2013
Executive Summary
The UCLA Computer Science Department is in the top-14 nationwide. In 2006–2014
our faculty received a National Medal of Science, an ACM Turing Award, a Scientific &
Technical Achievement Award from the Academy of Motion Picture Arts & Sciences, eight
NSF CAREER awards, two PECASE awards, five Sloan Research Fellowships, and ten testof-time awards. Additionally, we had one faculty member elected to Fellow of the Royal
Society, one to member of the National Academy of Engineering, and one to member of the
National Academy of Sciences. Also, five faculty were elected to ACM Fellow and three to
IEEE Fellow, one of our PhD students received an ACM Doctoral Dissertation Award, and
we placed three of our PhD graduates as assistant professors at Berkeley, Cornell University,
and University of Michigan. Our department has a strong momentum with many highly
productive superstars, seven large research efforts, steadily increasing research expenditures
($10.9 million in 2012–2013), and a goal to increase the funding guarantee for all PhD
students from two years to three years. The number of applicants for our undergraduate
programs has increased by a factor of four over the past nine years; our admission rate was
9% for Fall 2014. Some of this interest stems from the large potential for a high-paying job.
Most of the top-10 computer science departments have grown to meet the high demand;
particularly, the public schools in the top-10 have numbers of faculty that range from 49 to
96, which is significantly larger than Dean Dhir’s target of 38.5 FTE for our department.
Our small size is the biggest obstacle to achieve a top-10 ranking. Computing is an enabling
technology for modern life and for most sciences, and our faculty are increasingly engaged in
many interdisciplinary research efforts across UCLA. A strong computer science department
is a major resource for all of UCLA, and the potential for local impact extends to Silicon
Beach, which is the Santa Monica area that is home to over 500 startup companies and
many accelerators devoted to information technology. UCLA is perfectly located to interact
with this emerging source of jobs and wealth in Los Angeles and can do so effectively with
a strong computer science department. The tremendous interest in computer science is an
opportunity for UCLA: admit more undergraduate students to our programs and grow the
faculty size correspondingly. We have moved past a period of many retirements, departures,
and denials of tenure, we have hired four new faculty in the past four years to reach 30 FTE,
and we will continue to hire vigorously to get close to 38.5 FTE within two years. Our hope
is that UCLA will create a task force with the goal to determine the appropriate size for a
top-10 computer science department.
COMPUTER SCIENCE
LADDER FACULTY MEMBERS
Contents
A Introduction
1
B General Information
1
C Bylaws
12
D Undergraduate Programs
13
E Graduate Programs
21
F Postdoctoral Scholars
29
G Articulated, Concurrent & Self-Supporting Programs
30
H Diversity
30
I
33
Comparison to the Previous Review
J Resources
37
K Goals and Plans
37
L Special Circumstances
40
M Conclusion
40
N Resources
42
O Research Highlights
50
P Honors and Awards
54
Q Start-up Companies
68
A
Introduction
The preparation of this self-review involved many faculty, staff, and students in 2013–14.
First we gathered data in summer 2013 and had a one-day faculty retreat in October 2013 to
present and discuss the data and to plan for the future. Then we distilled information from
undergraduate exit surveys and alumni surveys; we held an undergraduate town hall meeting
in November 2013; we had an Undergraduate Advisory Board meeting and two Alumni
Association Board meetings; and we held a meeting of graduate student representatives in
May 2013. In spring 2014 we collected additional data and improved our bylaws. In May
2014 we distributed a draft of this report to all faculty members, then held a faculty meeting
to discuss the draft, and eventually revised the report based on faculty feedback. Finally, all
27 regular faculty members voted by secret ballot on this statement:
I had opportunity to provide input to this report, and the report generally reflects
my views.
The result was: 26-Yes; 0-No; 0-Abstain; 1-Absent.
B
General Information
The UCLA Computer Science Department is in the top-14 nationwide and has both PhD
and MS programs, as well as two undergraduate programs. Our professors provide significant
service to the profession and to UCLA.
Overview
Targets. Dean Dhir has set the following targets for our department:
38.5 faculty
380 graduate students
700 undergraduate students
Number of faculty. Since the last review, the department has gone from 34 regular
faculty members, plus two permanent lecturers (in UCLA parlance, lecturers with security
of employment), one joint faculty member, and six adjuncts, to 27 regular faculty members,
plus two permanent lecturers, six joint faculty members, and 11 adjuncts. We currently
also have 13 emeriti. We emphasize two subtleties. First, our two lecturers with security
of employment counts as full-time equivalents (FTEs), so currently our number of FTEs is
27+2 = 29. In summary, we currently have 27 regular faculty members yet 29 FTEs. Second,
we write this report during the recruiting season; we have already hired one candidate and
have an offer out to another candidate, and we plan to make additional tenured offers later
this summer, if approved. Thus, once the new professor joins we will be 28 regular faculty
members yet 30 FTEs, and those numbers may go up soon. However, in this report, our
count is 27 regular faculty members yet 29 FTEs. Before this recruiting season started, we
had permission to hire eight faculty members in 2014–2016, so now we have seven to go.
1
No. of papers
2010-2014
41+
3
1
3
1
21-40
1
2
2
1
11-20
2
2
2
2
0-10
5
11-20
21-40
41+
0-10
No. of PCs
2006-2014
Figure 1: Number of PC memberships in 2006–2014 and number of papers in 2010-2014.
Among the 27 regular faculty, we have 2 assistant professors, 3 associate professors, 10
full professors step 1–5, 6 full professors step 6–9, and 6 full professors above scale. The 27
regular faculty consist of 21 white males, 4 Asian males, and 2 Asian females. Our short-term
academic staffing priority is to reach the target of 38.5 FTE that Dean Dhir has set for our
department.
Figure 1 visualizes aspects of the publication and service records of our 27 regular faculty.
Intuitively, the diagram plots each faculty member in two dimensions. The x-axis is the
number of conference program committee memberships, 2006–2014, while the y-axis is the
number of papers and books published in 2010–2014. For simplicity, we group the x-axis
into four intervals: 0–10 PCs, 11–20 PCs, 21–40 PCs, and 41+ PCs in 2006–2014. Similarly,
we group the y-axis into four intervals: 0–10 papers, 11–20 papers, 21–40 papers, and 41+
papers in 2010–2014. For each of the 4 × 4 regions in the diagram, we show a circle labeled
with the number of faculty in that region and with an area that is proportional to the number
of faculty.
Department organization. The department has a chair, a graduate vice chair, an undergraduate vice chair, ten standing committees, and many ad hoc committees. Additionally,
each of our eight research fields has a chair that handles teaching-related administrative
tasks. Until 2014 we also had a vice chair for industrial relations.
2
Research. We divide our faculty into eight fields: Artificial Intelligence, Computational
System Biology, Computer Networks, Computer Science Theory, Computer System Architecture, Graphics and Vision, Information and Data Management, and Software Systems.
Those fields are the same as at the time of the previous review and all eight fields remain
vibrant. In Appendix O, each regular faculty member describes his or her best research
result from 2006–2014.
We have seven large research efforts, namely the Center for Autonomous Intelligent Networks and Systems (CAINS, led by Mario Gerla), the Center for Information and Computation Security (CICS, led by Rafail Ostrovsky), the NSF Named Data Networking project
(NDN, led by Lixia Zhang), the NSF Center for Domain-Specific Computing (CDSC, led by
Jason Cong), the NSF Center for Encrypted Functionalities (led by Amit Sahai), the Scalable Analytics Institute (ScAI, led by Wei Wang), and the Wireless Health Institute (WHI,
co-led by Majid Sarrafzadeh). In 2002–2013 we also had the NSF Center for Embedded
Networked Sensing (CENS, led by Deborah Estrin).
Awards. Our faculty have won many honors and awards, in particular two Turing Awards,
namely Alan Kay (2003) and Judea Pearl (2011). The Turing Award is recognized as the
highest distinction in computer science and is viewed as “the Nobel Prize of computing.”
We also have eight ACM Fellows, namely Jason Cong, Deborah Estrin, David Heckerman,
Alan Kay, Leonard Kleinrock, Richard Muntz, Demetri Terzopoulos, and Lixia Zhang; sixteen IEEE Fellows, namely Algirdas Avizienis, Wesley Chu, Jason Cong, Milos Ercegovac,
Mario Gerla, Len Kleinrock, Allen Klinger, Richard Muntz, Judea Pearl, Majid Sarrafzadeh,
Stefano Soatto, Mani Srivastava, Demetri Terzopoulos, Alan Yuille, Lixia Zhang, and SongChun Zhu; four National Academy of Engineering members (Judea Pearl, Len Kleinrock,
David Heckerman, Alan Kay); two National Academy of Sciences Members (Stan Osher,
Judea Pearl); three AAAS members (Judea Pearl, Alan Kay, Len Kleinrock) and three
AAAI Fellows (Adnan Darwiche, Rich Korf, and Judea Pearl). In 2006–2013 we hired four
assistant professors.
We list our faculty’s honors and awards in Appendix P and their start-up companies
in Appendix Q, all from 2006–2014. Those lists include more than 75 major honors and
awards, such as prizes, medals, honorary doctorates, and elections to scientific societies
and academies, eight NSF CAREER awards, two PECASE awards, five Sloan Research
Fellowships, ten test-of-time awards, and also more than 25 best paper awards, more than
80 keynote and distinguished lectures, four teaching awards, and many interviews and other
honors.
We have four chaired professors: Jason Cong, Demetri Terzopoulos, Carlo Zaniolo, and
Lixia Zhang, and we have four vacant chairs.
Staff. Our department has 14 permanent staff members and 6 temporary work-study
helpers, while individual professors have a total of 5 assistants, funded by grants and contracts. Our staff is adequate for our current needs, yet once we hire 9.5 faculty FTE to reach
Dean Dhir’s target of 38.5, we will need additional staff support.
Diversity. We advertise our open faculty positions in several advertising outlets that
reach diverse groups. In Spring 2014, we interviewed four female faculty candidates and
offered positions to three of them; one is still considering, while two declined. We also
engage in many outreach activities to attract a greater number of women and members
of underrepresented groups to our undergraduate and graduate programs, and by further
3
providing excellent opportunities once these students join the department. We host many
events and strive to foster a diverse and inclusive environment.
Faculty teaching activities and numbers of students. We have three quarters in an academic year. The typical annual teaching load consists of three courses plus advising of PhD
students, MS students, and undergraduate students. The courses are typically an undergraduate course, an introductory graduate course, and an advanced graduate course.
In June 2013 we had 181 PhD students. The 27 regular faculty advise 153 PhD students
(average 5.5). Specifically, eight professors have 0–3 PhD students; eight professors have
4–5 PhD students; nine professors have 6–9 PhD students; and two professors have 17–21
students. Additionally, a total of five emeriti and adjuncts advise 16 PhD students (average
3.2), and a total of four joint faculty advise 12 PhD students (average 3).
In June 2013 we had 165 MS students. Each of those students must complete an MS
project or a more substantial MS thesis (the MS project is more common). We assign a
faculty member to be the advisor of each MS student. Each professor advises about six MS
students at any given time, on average.
The Computer Science Department has two undergraduate degree programs: Bachelor of
Science in Computer Science and Bachelor of Science in Computer Science and Engineering.
Among the 673 undergraduates enrolled in May 2014, 433 are CS majors and 240 are CSE
majors.
Instructor distribution in 2011-2012: research faculty taught 60% of the courses, permanent lecturers taught 28% of the courses, adjuncts and emeriti taught 8% of the courses, and
lecturers taught 4% of the courses. Only regular and adjunct faculty teach graduate courses
in our department.
The students evaluate every course offering. In May 2014 we produced a report with
summaries of the evaluations from 2006–2014. A highlight of the report is that the instructor
ratings are consistently higher than the course ratings.
The two national organizations ABET and CSAB accredite our undergraduate programs.
ABET is a nonprofit, non-governmental organization that accredits college and university
programs in the disciplines of applied science, computing, engineering, and engineering technology. CSAB serves as a participating body of ABET and is the lead society within ABET
for accreditation of degree programs in computer science, information systems, software engineering, and information technology. We passed the most recent ABET-and-CSAB review
in 2012 with flying colors and nothing major to improve.
Thanks to UCLA Engineering, we use an online system called CourseWeb to list our
course offerings and to maintain records for ABET purposes. Those records include syllabi,
exams, and examples of student work. The most recent ABET review of our department in
2012 used much less physical paper than previous ABET reviews thanks to CourseWeb: we
gave the review team online access to course material on CourseWeb.
Faculty equity with regard to gender and ethnicity. Regardless of gender or ethnicity, all
faculty members are expected to meet the same teaching standards and course load, as well
as contribute to the welfare of the department by attending faculty meetings, participating in
faculty candidate interviews, serving on committees, etc. Before some hires and departures
in the past two years, each of our three female faculty members had an endowed chair.
Resources. For 2012–13, excluding faculty and staff salaries and benefits, we had $0.4
million for department operating expenses, $1.8 million in instructional support, and $10.9
4
No. of faculty
6
5
4
3
2
1
0
1-3
4-6
7-9
10-12 13-15 16-18 19-21
No. of PCs
top conf.
2006-2014
Figure 2: The number of PC memberships for top conferences in 2006–2014.
million in research expenditures. Our space, network, computers, and teaching laboratories
are adequate for our needs. Some aspects of the building need repair, including the restrooms
and thermostats.
Top conferences
Top conferences are important in computer science. In computer science the top conferences
have become much like competitions to which the best people submit their best papers and
where getting a paper accepted is a major achievement that people notice. Membership of
a program committee for a top conference is a significant honor as well as a large service
effort. An even larger honor (and effort!) is to be the chair of a program committee for a
top conference.
We base our notion of top conference on publication and citation data from Microsoft
Academic Search. We rank a conference as a top-conference if 1) it has a high number of
highly cited papers and 2) it has a high number of citations per published paper, on average.
The 67 top conferences are: AAAI, AAMAS, ACL, ASPLOS, CAV, CCS, CHI, CONCUR,
CRYPTO, CSCW, CVPR, DAC, ECCV, ECOOP, EUROCRYPT, FOCS, FSE, HPCA,
ICALP, ICCAD, ICCV, ICDCS, ICDE, ICFP, ICML, ICPR, ICSE, IJCAI, INFOCOM,
IPSN, ISCA, ISLPED, ISMB, ISPD, ISWC, KDD, KR, LICS, MICRO, MOBICOM, NDSS,
5
NIPS, OOPSLA, OSDI, PLDI, PODC, PODS, POPL, RECOMB, S&P, Sensys, SIGCOMM,
SIGGRAPH, SIGIR, SIGMETRICS, SIGMOD, SODA, SOCG, SOSP, STOC, TREC, UAI,
UIST, USENIX, USENIX-security, VLDB, WWW.
Figure 2 illustrates our faculty members’ number of top-conference program committee
memberships in 2006–2014. For example, the right-most bar in Figure 2 illustrates that three
faculty members each served on 19–21 program committees of top conferences in 2006–2014.
In 2006–2014, five of our faculty were program chairs of top conferences. Todd Millstein was
program chair of OOPSLA 2014, Rafail Ostrovsky was program chair of FOCS 2011, Jens
Palsberg was program chair of POPL 2010, Stefano Soatto was program co-chair of ICCV
2011, and Wei Wang was program co-chair of KDD 2014.
Figure 3 illustrates our faculty members’ large numbers of papers in top conferences.
Rankings
We will discuss four recent rankings of computer science programs that are based on four
different criteria: reputation, characteristics, citations, and placement.
First, we discuss the reputation-based ranking that was published online by U.S. News
& World Report in 2014, http://grad-schools.usnews.rankingsandreviews.com. U.S.
News & World Report compiled that ranking based on a questionnaire about the reputation
of programs that they sent to deans, department chairs, and graduate vice chairs across the
United States. The ranking lists 177 computer science graduate programs and assigns a
ranking to 120 of those programs. Here are the top-14 schools in that ranking.
1.
1.
1.
1.
5.
6.
6.
CMU
MIT
Stanford
Berkeley
UIUC
Cornell
U. Washington
8.
9.
9.
11.
11.
13.
13.
Princeton
UT Austin
Georgia Tech
Caltech
U. Wisconsin, Madison
UCLA
U Michigan, Ann Arbor
This ranking places UCLA just outside the top-10, which is also true of previous U.S. News
& World Report rankings going back more than a decade.
Second, we discuss the characteristics-based R-ranking that was published by the National Research Council in 2010. The R-ranking is one of the two rankings that the NRC
published that year. The National Research Council compiled that ranking based on a
questionnaire about many program characteristics that they sent to universities across the
United States. Those program characteristics are research activity, student support and outcomes, diversity, average number of publications, percent of faculty with grants, awards per
allocated faculty member, percent of first-year students with full financial support, average
completion ratio in 6 years or less, median time to degree, percent with academic plans, and
number of PhDs graduated. Notice that those characteristics exclude citations. The ranking
lists 128 computer science programs. Here are the top-14 schools in that ranking.
6
1.
2.
3.
4.
5.
6.
7.
Stanford
Princeton
MIT
Berkeley
CMU
UIUC
Cornell
8.
9.
10.
11.
12.
13.
14.
UNC
UCLA
UCSB
U Pennsylvania
Harvard
U. Wisconsin, Madison
UT Austin
This ranking places UCLA inside the top-10.
Third, we discuss the citations-based ranking for the past ten years that is published and
updated online by Microsoft under the name Microsoft Academic Search, http://academic.
research.microsoft.com. Microsoft does that ranking automatically based on the results
of a search engine that finds research articles on the Internet and counts their citations. Here
are the top-14 schools in that ranking, as of May 2014.
1. Stanford
2. Berkeley
3. MIT
4. CMU
5. UIUC
6. UCSD
7. UCLA
8.
9.
10.
11.
12.
13.
14.
Georgia Tech
U. Washington
UT Austin
USC
Princeton
U Maryland
U Minnesota
This ranking places UCLA inside the top-ten.
Fourth, we discuss the placement-based ranking that was published by Brown University
in 2014, http://cs.brown.edu/people/alexpap/faculty_dataset.html. That webpage
has multiple rankings about the 2,200 faculty at the top-50 computer science departments
in the United States. Here we focus on the ranking labeled “Where do most professors get
their doctorate degree from?” The following table shows, for each of 13 schools, the number
of professors at the top-50 computer science departments who got their PhD at that school.
Rank
1.
2.
3.
4.
5.
6.
7.
Doctorate school
MIT
Berkeley
Stanford
CMU
UIUC
Princeton
Cornell
#professors
256
170
151
121
80
70
64
Rank
8.
9.
10.
10.
12.
17.
Doctorate school
U. Washington
Georgia Tech
Harvard
UT Austin
U. Wisconsin
UCLA
#professors
59
50
48
48
43
32
This ranking places UCLA as number 17 and well behind the top-10 schools in terms
of the number of professors placed at the top-50 schools. Note that this ranking is rather
consistent with the other rankings, particularly the reputation-based ranking by U.S. News &
World Report. Note also that the placement records of the top-four schools (MIT, Berkeley,
Stanford, and CMU) are significantly better than the others. This observation is consistent
with both the common view that those four schools are in a top-tier of their own and that
7
UCLA
top conf.
papers
in 2010-14
U. Washington
2
10
8+
3
10
10
2
4
6
1-7
7
3
11
1
2
0
1
5
1
0-19
20-39
h-index
0-19
20-39
40+
40+
Figure 3: Comparison of the computer science departments at UCLA and U. Washington.
those four schools are in the top-5 of all four rankings. Note finally that UIUC is in the
top-6 of all four rankings.
In summary, the reputation-based ranking has UCLA as number 13–14; the characteristics-based ranking has UCLA as number 9; the citation-based ranking has UCLA as
number 7, and the placement-based ranking has UCLA as number 17. We conclude that
our reputation currently lags behind our program characteristics and citations, and that we
should work to improve our placement record.
Citation records. A researcher has h-index n if his/her n most-cited papers all have
received at least n citations. Jens Palsberg maintains a partial list of computer science
researchers with an h-index of 40 or higher according to Google Scholar; the list is online at
http://www.cs.ucla.edu/~palsberg/h-number.html. In May 2014, seven schools worldwide had at least 17 people (including emeriti, zero-percent appointments, and adjuncts)
on that list, namely CMU (33), Stanford (32), Berkeley (26), MIT (25), UCLA (25), U.
Washington (25), and EPFL (21). We conclude that our department has one of the highest
numbers of professors that have made many, lasting contributions.
Comparison to U. Washington
Figure 3 shows a data-driven comparison of the computer science departments at UCLA
and U. Washington. We chose the U. Washington computer science department for the
comparison because it is a top-10 department at a public school. For our department to enter
the top-10, we must compare well with the U. Washington computer science department.
Intuitively, each of the two diagrams in Figure 3 plots each faculty member in two dimensions.
The x-axis is the h-index according to Google Scholar while the y-axis is the number of papers
in top conferences in 2010–2014 counted as explained below. For simplicity, we group the x8
axis into three intervals: h-index 0–19, h-index 20–39, and h-index 40+. Similarly, we group
the y-axis into the three intervals: 0, 1–7, and 8+ papers in top conferences in 2010–2014.
For each of the 3 × 3 regions of each diagram, we show a circle labeled with the number of
faculty in that region and with an area that is proportional to the number of faculty.
UCLA has 27 regular faculty while U. Washington has 51 regular faculty. Figure 3 shows
that the main similarity is that both departments have ten faculty who each has h-index
40+ and 8+ papers in top conferences in 2010–2014. These are people who have made
many lasting contributions and who have a major current presence in the top conferences;
we label them superstars. Figure 3 also shows the main difference between UCLA and
U. Washington, which is U. Washington’s strong pipeline of superstars. In particular, U.
Washington has 3 + 10 = 13 faculty with h-index 0–39 and 8+ papers in top conferences in
2010–2014, while UCLA has only two. Many of those faculty at U. Washington are destined
to become superstars because their papers in top conferences will likely be cited widely. We
conclude that UCLA has a competitive number of superstars now, yet U. Washington is well
positioned for the future, while UCLA’s pipeline of superstars is thin. Thus, one of our top
priorities is to fill our pipeline of superstars, that is, to hire assistant and associate professors
who publish many papers in top conferences.
Interdisciplinary Research and Collaboration
Many of our faculty are engaged in interdisciplinary and multidisciplinary research and
collaboration with researchers across UCLA and also outside UCLA. Here are some examples
of the collaborations with researchers at UCLA.
• Jason Cong has collaborated with Tony Chan in UCLA Mathematics on VLSI placement; with Frank Chang in UCLA Electrical Engineering on RF-interconnects; with
Deni Aberle and Alex Bui in UCLA Radiology and with Luminita Vese in UCLA Math
on medical imaging; and with Tad Blair in UCLA Psychology on neural simulation acceleration.
• Joseph DiStefano III and Eleazar Eskin have joint appointments in the UCLA Medical
School.
• Paul Eggert has collaborated with the Laboratory for Neuro Imaging in the UCLA
Medical School.
• Eleazar Eskin collaborates closely with many individuals in the medical school particularly on discovering the genetic variants underlying heart disease and psychiatric
disorders. These collaborations involve clinicians, biologists, geneticists, statisticians
as well as computer scientists.
• Alan Kay has collaborated with Sandro Duranti, Dean of UCLA Social Sciences.
• Len Kleinrock and Bradley Fidler at the Kleinrock Center for Internet Studies have
co-sponsored an interdisciplinary conference on the past, present, and future of electronic currency and payments, with the NSF-funded Participation Lab in the UCLA
Information Studies Department Participants will range from historians to engineers
9
to science fiction authors. Additionally, they collaborate with the UCLA Libraries
Special Collections to develop a physical and digital repository of documentation that
sheds light and helps us understand lessons from the development of the internet. They
also collaborate with the UCLA Center for Oral History Research to interview internet
pioneers.
• Miodrag Potkonjak has collaborated with Qibing Pei from UCLA Materials Science
and Engineering on efficient energy harvesters.
• Peter Reiher has worked with students from the English department to develop stories
that had ubiquitous computing aspects. The participants built ubiquitous computing
infrastructure and software, and designed and wrote stories.
• Majid Sarrafzadeh is a co-director of the UCLA Wireless Health Institute that is a
collaboration between the UCLA Medical School, UCLA Electrical Engineering, and
our department.
• Stefano Soatto was a member of the Laboratory for Neuro Imaging in the UCLA
Medical School before it moved to USC. Additionally, he has collaborated with Tony
Chan, Stan Osher, Luminita Vese, and Andrea Bertozzi in UCLA Math, with YingNian Wu and Alan Yuille in UCLA Statistics, with Ladan Sham in UCLA Psychology,
with J. P. Hubschman in the UCLA Jules-Stein Institute, and with T.C. Tsao in UCLA
Mechanical Engineering.
• Demetri Terzopoulos had two PhD students supported by gifts and grants from CedarsSinai for medical imaging collaborative projects and two PhD students supported by
gifts and grants from CASIT in the UCLA Medical school.
• Lixia Zhang has collaborated with Jeff Burke in UCLA School of Theater, Film and
Television.
A strong computer science department is a major resource for all of UCLA.
Our Department is Small Compared to our Competitors
Ever since the dot-com boom in the 1990s, almost all major research universities have made
significant investments in computer science. In contrast, Dean Dhir’s target number of FTE
for the UCLA’s Computer Science Department has increased only by one, from 37.5 to 38.5
since 2006. The size of UCLA’s Computer Science Department is now considerably smaller
than the nation’s top-10 departments.
The following is a list of the May 2014 faculty sizes of the computer science departments at
the universities in the U.S. News & World Report top-10 list, as well as our main competitors
in Southern California, UCSD and UC Irvine:
10
Rank
1.
1.
1.
1.
5.
6.
6.
School
FTE
CMU
79
MIT
84
Stanford
54
Berkeley
62
UIUC
61
Cornell
38
U. Washington
51
Rank School
8. Princeton
9. UT Austin
9. Georgia Tech
13. UCLA
15. UCSD
29. UC Irvine
FTE
31
49
96
29
55
73
Note that CMU has a School of Computer Science with both a Computer Science Department and a Machine Learning Department; our FTE count is for both departments. Note
also that Georgia Tech has a entire College of Computing with three separate schools; our
FTE count is for all three schools. Finally note that UC Irvine has a School of Information
and Computer Science that includes two computing-focused departments; our FTE count is
for both departments.
In order for UCLA to have a Computer Science Department with a top-10 ranking, we
believe that it needs to both make a significant investment and find ways to be more successful
at hiring and retention. The current FTE target for the department is 38.5, which is far
smaller than the departments at the public schools listed above. Their numbers of faculty
range from 49 to 96, which is significantly larger than Dean Dhir’s target of 38.5 FTE for
our department. The three outliers in the above list are UCLA and the two private schools
Cornell and Princeton, which have 29, 38, and 31 FTE, respectively. Note though that both
Cornell and Princeton are hiring vigorously. In particular, Joe Halpern, chair of the Cornell
Department of Computer Science, wrote in an email in June 2014 that: “The expectation is
that we will grow significantly, both in Ithaca and NYC, because are class sizes have grown
so quickly.” (We quote Halpern by permission.) Additionally, Andrew Appel, chair of the
Princeton Computer Science Department, wrote in an email in June 2014 that: “Princeton
was hiring aggressively this year.” (We quote Appel by permission.)
Executive Vice Chancellor Wyatt Hume appointed a Computer Science Task Force in
2000 that included 18 members from 13 departments and administrative offices across UCLA.
The Task Force’s 2001 report recommended that the computer science department grow to
47 FTE plus joint appointments and lecturers by 2006. In response, we added 14 new
faculty members and reached 36 FTE in 2006. Since then we have slipped to 29 FTE due to
retirements, departures, denials of tenure, and too few new hires. Our hope is that UCLA
will create a similar task force with the goal to determine the appropriate size for a top-10
computer science department.
11
C
Bylaws
Here is the complete text of our bylaws as approved by the computer science faculty in
May 2014 and as submitted for approval to the Academic Senate Committee on Rules and
Jurisdiction in June 2014.
I. The Chair
The chair is the executive officer of the department and is appointed by the
Dean of Engineering.
II. Standing Committees
The department has ten standing committees. The charges of those committees are as follows.
• Academic policy committee. Handles academic policy matters such as proposals for ad hoc majors and ad hoc minors, proposals for new courses, and
curriculum changes.
• Awards committee. Nominates faculty members for awards.
• By-law-55 committee. Votes on merit cases delegated to the committee.
• MS admission committee. Runs the MS admission process and makes the
admission decisions.
• PhD visit day committee. Runs the visit day for prospective PhD students.
The committee selects and works closely with a group of current PhD students.
• PhD admission committee. Runs the PhD admission process. Gets all regular faculty and possibly others involved in the admission process and eventually makes the admission decisions.
• PhD progress tracking committee. Runs the PhD progress tracking process.
Every year, the process begins with contacts between the committee, the PhD
students, and their advisors, continues with a faculty meeting at which all
faculty discuss every student, and culminates with a progress letter to each
student.
• Policy and planning committee. Advises the chair on strategy.
• Recruiting committee. Selects faculty candidates for interview. Gets all
regular faculty and possible others involved in the selection process.
• Written qualifying exam committee. Runs the PhD written qualifying exam.
Every year, all regular faculty vote on membership of the By-law-55 committee.
The typical number of members of that committee is five people who are all full
professors.
The department chair appoints regular faculty to the other committees by the
end of the Summer for the following academic year. Typically, the other committees have 3-4 members, though the MS and PhD admission committees may in
12
some years be much larger. The policy and planning committee usually includes
one or more former department chairs.
The department chair may be a member and may even be the committee chair
of one of more of the standing committees.
Each committee meets at the request of the chair of that committee. A quorum
is the chair plus at least half of the other members.
III. Faculty Meetings
The chair schedules faculty meetings and announces them at least a week in
advance, if at all possible. All faculty members can submit agenda items. A
quorum is half of all regular faculty who are in residence during the quarter in
which a meeting is held.
IV. Voting Procedures (UC Bylaw 55)
The UCLA Call, Appendix 4 on Voting Rights, defines the Minimum Voting
Constituency for all votes. The Computer Science Department lets exactly the
members of the Minimum Voting Constituency vote, except in the following cases:
1. For new regular, adjunct, and in-residence appointments, all regular faculty
vote.
2. When The UCLA Call allows, we delegate the vote to an elected By-Law-55
Committee.
All votes are by secret ballot. Voting is open for at least five business days, except
for voting on new appointments which may have a shorter voting period.
D
Undergraduate Programs
The Computer Science Department has two undergraduate degree programs: Bachelor of
Science in Computer Science and Bachelor of Science in Computer Science and Engineering.
The former is more software oriented; the latter is more hardware oriented and includes a
significant number of required courses in electrical engineering. Dean Dhir has set a target
of a total of 700 undergraduate students across the two majors. The number of students
varies throughout a school year, mainly because students can graduate after each of the three
quarters. We had 718 undergraduate students in September 2013 and 673 undergraduate
students in May 2014. Among the 673 undergraduates enrolled in May 2014, 433 are CS
majors and 240 are CSE majors.
Applications. The number of applications has more than tripled in five years:
CSE
applications
admitted
enrolled
CS
applications
admitted
enrolled
F10
1,013
277
72
F11
1,259
313
77
F12
F13
F14
1,843 2,208 2,693
260
307
293
59
59
59
734 1,000 1,568 2,149
183
250
224
270
51
70
49
56
13
3,301
275
52
The above table shows that for Fall 2014 we received 5,994 applications, of which we
admitted 568 (9%), and 111 plan to enroll (20% yield). For Fall 2014, UCLA Engineering as
a whole received 19,715 applications, of which 2,593 (13%) were admitted, and 683 plan to
enroll (26% yield). Our two undergraduate majors have the lowest admit rates among the
majors in UCLA Engineering.
The median SAT score of students that enrolled for Fall 2014 was 2235 for CS and 2240 for
CSE, while the median for UCLA Engineering as a whole was 2170. The median unweighted
GPA of students that enrolled in CS or CSE for Fall 2014 was 4.0, which is the same as
for UCLA Engineering as a whole. The following table shows how these numbers and other
numbers have improved over the past three years:
Weighted GPA
UCLA
Unweighted GPA
UCLA
SAT Composite
UCLA
SAT Math II
UCLA
CSE
CS
Engineering
CSE
CS
Engineering
CSE
CS
Engineering
CSE
CS
Engineering
Enrollment
2012 2013
4.45 4.53
4.41 4.46
4.40 4.44
4.00 4.00
3.95 4.00
3.95 3.96
2180 2190
2160 2200
2125 2140
800 795
780 800
780 790
year:
2014
4.58
4.54
4.45
4.00
4.00
4.00
2240
2235
2170
800
800
790
Graduates. Number of graduates:
CS
CSE
Total
2004–05 2011–12
80
99
84
36
164
135
2012–13
114
28
142
Notice that we graduate more students than enroll as freshmen. The reason is the high
number of students who change majors to CS or CSE. Notice also that while we enroll
roughly the same number of freshmen in CS and CSE, we graduate far more CS majors.
Again, the reason is the high number of students who change majors, including some who
change majors from CSE to CS.
Class sizes. Class sizes in Fall 2012:
First year freshman seminar (all freshmen): 130
First year, CS31 (the first CS course, for all engineering students): 129, 175
First year, CS33 (the third CS course): 99
Lab courses: 10, 16, 18, 18, 27, 28, 31, 31
Second year, M51A: 66
Third and fourth year courses: 53, 70, 79, 80, 100, 103, 106, 116
14
Goals. Our two undergraduate programs have slightly different goals. For Computer
Science, the educational goal is to produce graduates who are well grounded in core computer
science knowledge and have the problem-solving and other professional skills that will enable
them to achieve their full potential and to excel in their chosen career paths. For Computer
Science and Engineering, the educational goal is to produce graduates who are well grounded
in core computer science knowledge, but who also have an understanding of electrical and
electronic circuits. They should have the problem-solving and other professional skills that
will enable them to achieve their full potential and to excel in their chosen career paths.
The rationale for those goals is that computer science has both significant breadth and
depth, as well as a wide variety of applications areas. The structure of our programs reflects
that rationale. For both programs, the required computer science backbone is:
• First year: courses on programming and computer organization.
• Second year: a software construction laboratory and a course on logic design.
• Third year: courses on operating systems, networking, programming languages, architecture, algorithms and complexity, and formal languages and automata theory.
• Fourth year: a course with a capstone project on either software engineering or digital
design.
Additionally, students have electives and must take courses from other disciplines. The main
difference between CS and CSE is that while CS has many electives, CSE sets most of these
electives to be well-chosen courses in electrical engineering.
Our programs are effective: students responded positively in our undergraduate town hall
meeting in November 2013. Additionally, all the graduates who responded to our exit-survey
either found jobs or entered graduate school.
Learning objectives. Our programs have slightly different learning objectives:
• The overall objective of the Computer Science program is to graduate students who are
(1) prepared for entry-level positions as practicing computer scientists or for continued education in graduate programs through core scientific and engineering knowledge,
laboratory and design experience, a solid grounding in the principal areas of computer
science, and exposure to the current state of the art; (2) positioned for sustained career achievement through cultivation of critical professional skills, including teamwork,
written and oral communications, problem-solving abilities, a commitment to lifelong
learning, core ethical values, and an understanding of the implications of one’s work
on society; and (3) prepared for practice in one of the fertile application areas where
computing and other technical fields intersect through in-depth knowledge of at least
one related engineering discipline or application area.
• The overall objective of the Computer Science and Engineering program is to graduate
students who are (1) prepared for entry-level positions as practicing computer scientists or computer engineers or for continued education in graduate programs through
core scientific and engineering knowledge, laboratory and design experience, a solid
grounding in the principal areas of computer science and engineering, and exposure to
15
the current state of the art; (2) positioned for sustained career achievement through
cultivation of critical professional skills, including teamwork, written and oral communications, problem-solving abilities, a commitment to lifelong learning, core ethical
values, and an understanding of the implications of one’s work on society; and (3) prepared for practice in computer systems engineering at the interface of digital hardware
and software and the electronic circuits that interface computers to the analog world.
Students will be prepared to contribute in the fertile application areas where computing and other technical fields intersect through substantial knowledge of at least one
additional engineering discipline or technical application area.
Accreditation by ABET and CSAB led us to formulate the above objectives and to run an
annual process of faculty and student consultation. The structure of our curriculum ensures
that students receive a broad education in computer science, and a solid grounding in the
principal areas of computer science, as well as a capstone project experience that sharpens
their teamwork and professional skills and prepares them for practice,. The goals of our
individual courses ensure that students receive the in-depth knowledge they need. We have
a constantly changing suite of elective courses that reflect the current state of the art. In
2006–2014, new elective courses included:
CS114 Peer-to-Peer Systems
CS CM121 Introduction to Bioinformatics
CS CM122 Algorithms in Bioinformatics and Systems Biology
CS CM124 Computational Genetics
CS136 Introduction to Computer Security
CS144 Web Applications
CS145 Introduction to Data Mining
CS183 Introduction to Cryptography
CS188 Game Design
CS188 3D Real-Time Animation
All our students take an ethics course that teaches core ethical values and an understanding
of the implications of one’s work on society. The ethics course also has an interdisciplinary
teamwork assignment with students from different majors. Several of our courses have a
substantial writing component, including the freshman seminar CS1 and the ethics course.
One possible weakness is that we have few courses that help strengthen oral communication
skills.
Overall procedure for assessment of student learning. Both our programs use a capstone
experience as the overall assessment procedure for student learning. Students can choose
either CS130 Software Engineering or CS152B Digital Design Project Laboratory; both
courses offer a large design project that the students carry out in groups. For example, in
each offering of CS130, multiple companies provide software projects, send people to UCLA
to interact with the students three times during the quarter, and generally are available to
define the goal of each project, set expectations, help along the way, and evaluate the result.
In 2011–2014 those companies and institutions included Aerospace Corporation, Cisco, IBM,
UCLA Laboratory for Neuro Imaging, San Diego Zoo, Shopzilla, and Ticketmaster. The
company interactions are highly valuable for the students and for the overall quality of the
16
course. When a group produces good software, which almost all the groups have done over
the years, we see it as a sign that they have acquired both the computer science knowledge
and the professional skills that they need to succeed.
From learning assessment to teaching improvements. We run an annual self-examination
and assessment of our undergraduate programs.
First, for each course offering, both the instructor and the students evaluate the course.
The teaching assistant archives assignments, exams, and examples of student work, and the
instructor assesses how well students achieved various program outcomes. The students rate
many aspects of the course, including how well they learned the topics taught in the course,
the overall effectiveness of the instructor, etc.
Second, when a student graduates he/she ranks how prepared they feel they are in various
areas that span both specific technical areas and professional skills areas such as communication and teamwork.
Third, UCLA Engineering sends surveys to our alumni who rank such things as the
quality of recent graduates that they have hired in their companies. The most recent survey
targeted 2009–2010 alumni and ended in 2013.
Fourth, the faculty of each research field does an annual evaluation of the course offerings
and produces written suggestions for improvement. ABET and CSAB require us to use those
suggestions in future course offerings and then evaluate how well they worked. In the period
2006–2014 we made significant improvements to 32 different undergraduate courses. For
example, we improved course CS 132 Compiler Construction by introducing well-established
formal notation to present the rules for type checking programs. The new course material
helped the students better understand some of the theoretical foundations of programming
languages, helped them better appreciate the algorithms used for type checking, and served
as a better basis for doing the type-checking homework. The students have responded
positively to the new material.
Fifth, we have an annual advisory board meeting where we review our programs with
representatives of all stake holders, including employers, alumni, students, and faculty.
Sixth, we have an annual town hall meeting with undergraduate students and faculty to
discuss the issues that the students raise.
Seventh, the culmination is a faculty meeting in which we analyze the data and discuss
plans for short-term and long-term improvements. Major conclusions that we have drawn
recently include:
1. All the graduates who responded to our alumni survey are satisfied with the education
they received in our programs.
2. Over 38% felt that their skill level was higher than that of peers from programs in
other universities, while 50% thought that the skill levels were about the same.
3. About 22% of our graduates go on to earn advanced degrees. In 2006–2014, some of
our students entered the PhD programs at Duke (1), MIT (3), Stanford (1), UCLA
(7), and University of Pennsylvania (1), and one went on to Harvard Medical School.
4. The strongest aspects of our programs are the foundational material, the software engineering courses, and the opportunities to learn multiple programming languages and
17
to take courses in statistics. Our alumni say that the education was good preparation
for graduate school and internships. One recent alumnus (2009) wrote:
“It’s been my experience that a BS in CS from UCLA is equal to a Master’s
from other colleges.”
5. The weakest aspects of our programs are that they offer too little on web technologies, give poor preparation for entrepreneurship and the startup culture, have only
one project-oriented course on software engineering, and require many courses outside
computer science.
Contributions to undergraduate education at the campus level. Several major and minor undergraduate degree programs at UCLA require some of our courses, and this has
worked well with little or no coordination between these programs. Those programs include
the Linguistics and Computer Science major, the Mathematics of Computation major, the
Computational and Systems Biology major, and the Bioinformatics minor.
All engineering majors take either our first computer science course CS31 or a Matlab
course.
We used to offer a course, CS2, that introduces computer science to students outside
engineering; the last offering was in 2010.
Recently, we let students from outside the programs mentioned above into CS31 and
CS32. In 2013-2014, we had 192 such students in CS31 and 76 students in CS32. Those
numbers are large and serve as a reminder of the significant demand for computer science
courses across UCLA.
Online learning. Most of our undergraduate courses have websites with syllabus, lecture
schedule, homework, and other course material.
Flipped classrooms. We have some “flipped classrooms,” that is, courses where students
learn new material by watching online video lectures, usually at home, and do assigned
problems in class where instructors offer personalized guidance and interaction. CS35L
has always been hybrid, in that it is about half standard lecture and half flipped classroom
(though we call it a “lab”). The flipped classroom sometimes works well (it helps students to
stop beating their heads against the wall), sometimes works less well (students simply leave).
Much depends on the teaching assistant who is running the session. Flipped classrooms seem
less appropriate for more advanced material.
Diversity. Most of our undergraduate courses are technical and don’t include issues of
diversity. We do mention that two of the pioneers of computing were women, namely Ada
Augusta and Grace Hopper.
Student organizations. Our three main student organizations are:
Association for Computing Machinery (ACM): faculty advisor, Glenn Reinman
Upsilon Pi Epsilon (UPE): faculty advisor, David Smallberg
Linux User Group (LUG): faculty advisor, Paul Eggert
ACM is the world’s largest educational and scientific computing society (http://www.acm.org).
We are happy that UCLA has a local chapter centered in our department. Many professors
in our department are members of ACM and also major contributors by being journal editors, conference organizers, etc. UPE is the international honor society for the computing
18
and information disciplines (http://upe.acm.org). LUG provides help and educates people
on the popular Linux operating system.
All three student organizations host many events throughout the year and have a major
positive effect on the quality of the UCLA experience for our undergraduate students.
Student tutoring. UPE, as well as two other student organizations, namely HKN (the
national Electrical Engineering and Computer Engineering Honor Society) and TBP (the
engineering honor society that represents the entire engineering profession) have extensive
tutoring programs: students can come in Monday to Friday from 10 am to 5 pm for help
with computer science, math, physics, etc. UPE also conducts midterm review sessions for
CS31, 32, and 33.
ACM has events known as ACM Teach where experienced students run hour-long tutoring
sessions. The sessions cover such topics as programming software for iPhones, JavaScript
programming, and editors including vi and emacs. Additionally, in preparation for the
world-wide ACM Intercollegiate Programming Contest (ICPC), ACM coaches potential participants on different topics and algorithms throughout the year and organizes qualifiers and
competitions to form teams for ICPC.
ACM also has artificial intelligence groups that are mainly collaborative learning groups
in natural language processing, machine learning, and gaming. Students meet every other
week to work together and help each other.
Student mentoring. UPE does mentoring of UCLA CS students, in collaboration with
MentorSEAS which is UCLA Engineering-wide.
Faculty advising. Every faculty member meets with about 30 undergraduate students
for three hours every quarter to talk about anything—from graduate school, disappointing
classes, where to go for internships, or anything else that may be on their minds. The students
are required to attend one of those meetings per year. In practice, about 10 show up for
any given meeting, which is small enough to make an enjoyable and productive experience
for all. Associate Dean Wesel started these meetings in 2008, and the response has been
overwhelmingly positive.
Industry internships. Every January we have an internship day when companies come
to UCLA and make a pitch for students to join them for a summer internship. In summer
2012, 74% of our undergraduate students had industry internships. The remainder were
typically either students who just completed their first year or students who joined a research project over the summer. In summer 2012, computer science students interned at,
for example: Amazon, Boeing, Cisco, DirecTV, Google, HP, LinkedIn, Northrop Grumman,
Qualcomm, Sandia, Symantec, and Teradata; while CSE students interned at, for example:
Cisco, DirecTV, Google, Jet Propulsion Laboratory, Los Angeles Dept of Water and Power,
RAND Corporation, Sony, Southern California Edison, and Vizio.
Research participation. Among our undergraduate students, in 2011–12, 28% participated
in research, while in 2012–13, 24% participated in research. These percentages reflect well
the percentage of our students that appear to seriously consider graduate school.
Comparison. Our undergraduate programs are the only ones at UCLA with their particular educational goals and learning objectives. Across the United States, most universities
and colleges have undergraduate programs in computer science, but in comparison our programs stand out, both in terms of quality and in terms of our constantly changing suite of
elective courses that reflect the current state of the art.
19
As an example of how we adapt our teaching to big changes, let us focus on the big shift
towards parallel, concurrent, and distributed computing that has taken place in society over
the past decade. For example, multi-core computers, data centers, and cloud computing are
now mainstream and evidence of this shift. Our programs have adapted quickly to reflect
this reality, and more quickly than most other computer science programs in the United
States, we believe. Many of our courses teach aspects of parallel, concurrent, and distributed
computing; here we list both undergraduate courses and graduate courses (numbered 2xx):
• CS33 Introduction to Computer Organization. A two-week intensive introduction to
parallel programming. OpenMP and CUDA plus an open-ended lab where students
take an application and work to reach a fairly conservative performance goal. Those
who go beyond that goal (which requires attacking more difficult-to-extract parallelism)
get extra credit.
• CS35L Software Construction. Multithreaded performance using GNU sort—parallel
in the lab and POSIX-thread-parallelizing a ray tracer as homework.
• CS111 Operating Systems. Both multithreaded and distributed operating systems,
with a programming project focusing on distributed computing and defensive programming. This includes general topics on concurrent programming, such as the use
of locks and semaphores, and deadlock, livelock, and related problems involving concurrent behaviors, as well as principles of distributed systems (consensus and voting
algorithms, for example) and distributed file systems.
• CS130 Software Engineering. Parallel, distributed, and decentralized software architectures, with software projects often using technology such as Amazon Web Services.
• CS131 Programming Languages. Distributed processing such as MapReduce and forkjoin concurrency.
• CS133 Parallel and Distributed Computing. Parallel, concurrent, and distributed computing, including foundations, algorithms, languages, multicore computers, data centers, cloud computing, etc.
• M151B Computer Systems Architecture. Introduction to pipelining, multiprocessor,
and cache coherence.
• CS219 Selected Topics on Cloud Computing. Parallel or distributed computing: MapReduce, Google file system, Bigtable, and other real cloud systems built at Amazon,
Facebook, Microsoft, Google, etc.
• CS251A Advanced Computer Architecture. Instruction-level parallelism: pipelining,
superscalar, VLIW.
• CS251B Parallel Computer Architectures. Vector machines, GPUs, multicore.
• CS256A Advanced Scalable Architectures. Multicore, HPC, data centers, warehousescale computers.
20
• CS261A Problem Solving and Search. Parallel and distributed search algorithms.
• CS280D Distributed Computing: Foundation—models and solution techniques in sharedmemory and message-passing systems, with emphasis on classifying models according
to their power to solve consensus.
• CS281 Communication Complexity Theory: The minimum amount of communication,
as measured in bits, required in order to compute functions whose arguments are
distributed among several parties.
• M282A Cryptography: Byzantine agreement and secure multi-party computation.
Those courses give our students a strong education in parallel, concurrent, and distributed
computing.
E
Graduate Programs
The goals of our graduate programs are to provide world-class PhD and MS educations in
computer science.
Number of graduates. In 2006–2014 we graduated 239 PhDs and 613 MS students. For
three individual years, we have these numbers of graduates:
2004–05 2011–12 2012–13
PhD
28
28
30
MS
99
87
73
Number of current students. In June 2013 we had 181 PhD students (160 active, 11 on
filing fee, 10 on leave of absence), and we had 165 MS students (150 active, 15 on filing fee).
Dean Dhir has set a target of 380 graduate students in computer science.
In 2005 we had 196 PhD students and 91 MS students. Thus, the total number of
graduate students is growing, though via a small decrease in the number of PhD students
and a large increase in the number of MS students. The decrease in the number of PhD
students from 2005 to 2013 is due mostly to a decrease in the number of faculty. As we fill
our open faculty positions, we will work towards the ratio of 2:1 PhD to MS students that
Dean Dhir suggested in his steady-state memo dated Dec 13, 2013. As a step on the way, we
hope to reach 215 PhD students and 165 MS students within the next four years. We plan
to let the number of faculty members and the number of PhD students grow hand in hand.
The idea is that the new faculty members can help increase our research expenditures, which
in turn will pay for the additional 34 PhD students.
Among our current graduate students, we have 53.5% foreign students and 16.8% female
students.
Learning objectives. These are the learning objectives for our graduate programs:
Computer science is concerned with the design, modeling, analysis, and applications of computer-related systems. Its study at UCLA provides education
21
at the undergraduate and graduate levels necessary to understand, design, implement, and use the software and hardware of digital computers and digital
systems. The programs provide comprehensive and integrated studies of subjects in computer system architecture, computer networks, distributed computer
systems, programming languages and software systems, information and data
management, artificial intelligence, computer science theory, computational systems biology and bioinformatics, and computer vision and graphics.
Our objectives are rather similar to what we know about learning objectives in computer
science departments at other universities, though some departments will have research fields
that differ from ours. We have a strong track record of meeting those objectives.
While the learning objectives don’t mention hands-on experience and use of practical
software and hardware tools, those elements are an integral part of our programs.
Major and minors. Each PhD student selects a major and two minors among these
eight fields: Artificial Intelligence, Computational System Biology, Computer Networks,
Computer Science Theory, Computer System Architecture, Graphics and Vision, Information
and Data Management, and Software Systems. Additionally, we allow some ad hoc minors,
with petition. Each student takes six courses in the major and three courses in each of the
minors.
Note that MS students don’t have major and minors; they simply have a course requirement and a project-or-thesis requirement.
PhD admission. The admission of PhD students is done by a combination of individual
faculty members and a committee that sets a department-wide bar.
The following table describes our PhD applicant pool for Fall 2014:
Citizenship
Foreign
US/PR
Total
Fall 2013 Fall 2014
296 82% 364 85%
66 18% 64 15%
362
428
Gender
Male
Female
Total
286 79% 358 84%
76 21% 70 16%
362
428
MS
BS
Total
196
166
362
Highest degree
54% 237
46% 191
428
55%
45%
A total of 59% of the applicants for Fall 2014 expressed interest in one of the research
areas of artificial intelligence, networking, or graphics and vision, while the similar interest
number for Fall 2013 was 66%. The number of high-quality applicants in each of our research
areas is sufficiently high that each professor can usually get close to his/her target number
of new PhD students.
Among the 428 PhD applicants for Fall 2014, we offered admission to 46 students (11%
admission rate), and among those, 24 accepted admission (52% yield).
22
We have an annual visit day for prospective PhD students, and additionally, some students visit individually. A total of 12 people attended the visit day in 2014 (and 3 people
visited individually), and a total of 11 people attended the visit day in 2013 (and 2 people
visited individually). Each visit day is packed with faculty talks, campus tours, lunch with
current PhD students, lab tours, individual meetings with faculty members, dinner, etc.
The following table describes our PhD yield (students who accept offers of admission and
enroll):
Citizenship
Foreign
US/PR
Total
Fall 2013 Fall 2014
19 86% 22 92%
3 14% 2
8%
22
24
Gender
Male
Female
Total
17
5
22
77%
23%
22
2
24
92%
8%
MS
BS
Total
11
11
22
50%
50%
12
12
24
50%
50%
Highest degree
The 24 new PhD students for Fall 2014 are from some of the finest institutions in the
world, including domestic universities—Berkeley, MIT, UCLA, U. Minnesota, UC Irvine;
domestic undergraduate colleges—Harvey Mudd College; universities in China—Beijing Univ
Aero & Astronautics, Fudan University, Sun Yat-Sen University, Tsinghua University, USTC,
Wuhan University, Xidian University, Zhejiang University; universities in South Korea—
Chungang University, Seoul National University; universities in India—IIT Bombay, IIT
Madras, Jadavpur University; and these other universities—Sharif University of Technology
(Iran), National Technical University Athens (Greece), University of Alberta (Canada), and
Tanta University (Egypt).
The percentage of new US/PR students is low, yet if we set a target for admission of
US/PR PhD students, it would intrude on each faculty member’s privilege to select their
own PhD students.
The number of new female PhD students plummeted from 2013 to 2014, right at the
time when two of our female professors left and one female professor joined. The number of
female applicants also dropped from 2013 to 2014, as shown in an earlier table. We believe
that the female professors serve as important role models in the department, and that the
presence of a significant number of female professors will increase the chance that excellent
females will apply for the PhD program. Thus, the drop in new female PhD students is a
strong reminder that we must hire more female faculty.
MS admission. The admission of MS students is done by a department-wide committee.
Among the 1,073 MS applicants for Fall 2014, we offered admission to 268 students (25%
admission rate), and among those, 147 accepted admission (55% yield).
Timeline and milestones. The normative time to PhD is 6 years, while the normative
time to MS is 1 year and two quarters. Among the 239 PhD students who graduated in
23
2006–2014, 78% graduated within 6 years. Among the 613 MS students who graduated
in 2006–2014, 40% graduated within 1 year and two quarters, while 82% graduated within
two years. The main reason why more than half of the MS students take longer than the
normative time appears attributable to ambitious MS projects. This is acceptable because
the MS student and his/her advisor jointly decide on how long to continue a project.
For PhD students, the major milestones are to pass the written qualifying exam after
two years, pass the oral qualifying exam after four years, and defend and file a dissertation
after six years.
Most students complete their coursework in a timely manner, and incomplete grades are
rare.
The following is attrition data for 2006–2013:
Number of students
PhD students started
Dropped out with an MS
Dropped out, no degree
MS students started
Dropped out
2006
38
9
3
77
6
2007 2008
51
55
5
10
5
3
86
69
13
2
2009
49
10
2
93
5
2010 2011 2012 2013
45
32
33
24
1
6
1
0
5
4
0
2
110
68
67
94
15
6
0
0
The main factor that contributes to longer-than-normative times to doctoral candidacy
and degree completion, and to attrition, is the lure of high salary in industry; some students
begin work while studying and get delayed, or never return to UCLA.
Financial support. In June 2013, we funded our 181 PhD students from the following
sources:
TA
GSR
no support
unknown
GSR other department
graduate division
external agency
UCLA Engineering
TA other department
development
28%
27%
12%
8%
7%
6%
5%
4%
2%
1%
This table shows that most of our students are funded, yet we strive to fund all our PhD
students. Since 2011, we have guaranteed two years of support to every incoming PhD
student, unless he/she already has support from an outside agency.
The most common case is that a PhD student receives full tuition and stipend throughout
his/her PhD studies, including a fellowship in the first year, a teaching assistant in the second
year, and a GSR in the other years. During the summer, some students are on paid industry
internships, while others get summer stipends either from research assistantships or summer
teaching assistantships.
PhD students who receive GSR funding from the Computer Science Department are
currently paid $2,164.82/month, which, in the parlance of University of California, is Step 7
24
at 49%. That amount has worked well for several years, yet recent feedback from our PhD
students is that housing costs have increased at a much higher rate than the stipend. On
July 1, 2014, UCLA will increase the amount to $2,229.99/month as part of a general pay
raise of 3%. Additionally, in May 2014 we started to investigate whether an increase to Step
8 is feasible.
Among the 24 new PhD students for Fall 2014, we gave 22 a total of 2 years of guaranteed
support, while the remaining 2 had full support from outside agencies. Support in later years
hinges on satisfactory progress.
Efforts to foster student success. Each new PhD student is assigned an advisor and joins
a lab from day one. That way, each new PhD student has an immediate group of PhD
students from whom to seek advice, etc. Additionally, our written qualifying exam requires
each student to write a research or survey paper; this encourages our students to get involved
in research right away.
Our graduate office provides advice to all graduate students throughout their time at
UCLA.
Each prospective teaching assistant must take a quarter-long course that prepares that
student for a teaching assistantship. We require every PhD student to be a teaching assistant
for at least one quarter, or have equivalent teaching experience.
We track the progress of PhD students. We have faculty meetings that review the progress
of every PhD student each year. The objective of progress tracking is to give feedback to the
students on their progress, to identify the strongest and the weakest students, and to build
and maintain a shared sense of standards among the faculty.
Our department has a strong track record for placement of PhD students in academic
positions, and each faculty member helps their students understand the options and how to
go through the application and interview process.
Almost all our PhD students publish and present a substantial number of papers in conferences. Their participation in conferences, and particularly their presentation of research
results at the conferences, gives them considerable exposure to the research community and
opportunities for networking.
Most of our graduate students are on paid industry internships for at least one of their
summers at UCLA. Some of those internships are research-oriented while others are productoriented.
Our department has the following annual awards for graduate students: Outstanding
Graduating Masters Student, Outstanding Graduating Ph.D. Student, and four Outstanding Graduate Student Research awards. Additionally, UCLA Engineering has the HSSEAS
Edward K. Rice Outstanding Doctoral Student award. Every year we nominate the Outstanding Graduating Ph.D. Student for the Edward K. Rice Outstanding Doctoral Student
award.
Both our department and UCLA’s Career Center have many events where companies
pitch career opportunities to the students. We broadcast advertisements of those event to
our students.
In 2012 we started to track the career trajectories of our alumni and we plan to publish
the placements of recent alumni to current and prospective students.
Online learning. Most of our graduate courses have websites with syllabus, lecture schedule, homework, and other course material.
25
Some of the computer science faculty members contribute to the UCLA Engineering’s
Master of Science in Engineering Online Program. In this online program, students can
earn a Master of Science in Engineering degree with the same program of study as in the departmental programs, with the same courses, same instructors, and same grading standards.
The students are located throughout the country, which shows that the program expands
the reach of our department outside of the Los Angeles area.
Participation in departmental affairs. Our graduate students participate in two important activities: interview of faculty candidates and evaluation of PhD applications. First,
each faculty candidate meets with a small group of PhD students, both to give the candidate
an impression of our students, and to enable our students to give feedback on the candidate’s
potential as advisor, etc. Second, some of our senior PhD students evaluate a modest number
of PhD applications, typically from their own country. This works well in part because our
students occasionally point to weaknesses or strengths that the faculty overlooked.
The graduate students have formed the Computer Science Graduate Student Council
(CSGSC) that serves some of the needs of our graduate students, such as organization of
social events and bringing forward requests to the department. Almost all those social events
bring together graduate students, post-docs, and faculty. The CSGSC leaders are in frequent
contact with the department chair.
Interdisciplinary teaching. Some of our graduate students have been teaching assistants
in the Engineering Ethics course offered by UCLA Engineering. Additionally, some of our
graduate students are teaching assistants in other departments, such as biology and foreign
languages, though none participated in the Collegium of University Teaching Fellows in
2006–2014.
Awards. Some of our students have received prestigious awards. The following list focuses
on extramural awards.
Sanjam Garg received the 2013 ACM Doctoral Dissertation Award: PhD advisor, Amit
Sahai.
Dan Marino received the 2012 ACM SIGPLAN Doctoral Dissertation Award: PhD advisor, Todd Millstein.
Guojie Luo received the 2013 ACM SIGDA Outstanding PhD Dissertation Award in
electronic design automation: PhD advisor, Jason Cong.
Additionally, most of the best-paper awards listed in Appendix P are co-authored by one
or more of our graduate students.
Student feedback. In May 2014, the Chair met with 10 PhD computer science PhD students from 9 different research groups, representing a total of about 76 PhD students (42%
of our department’s PhD students). Additionally, one of the students represented the Computer Science Graduate Student Council (CSGSC). The graduate student representatives
had solicited input from their peers and lab mates ahead of the meeting.
The students mentioned ten positive aspects:
• The funding guarantee for all our PhD students ensures that nobody has to scramble
for money in the first two years of study.
• The administrative staff, particularly Steve Arbuckle who heads our Graduate Office,
helps the graduate students in many ways.
26
• Most documents and procedures are online, which enables students to easily navigate
the administrative aspects of their studies.
• The written qualifying exam encourages research from day one.
• The many social events, including the CS201 seminar series, the Postel distinguished
lectures, the weekly tea time, the holiday party, the winter social event, and the poster
session. The students asked for more social events, particularly a barbecue.
• The visit day for prospective PhD students.
• The frequent emails about job opportunities, along with the many career events, etc.
• UCLA keeps going up in the rankings!
• Good teaching: Particularly the recently hired professors put a lot of effort into their
graduate courses.
• The graduate curriculum overall.
The students also mentioned ten negative aspects:
• The hardcopy timesheets that must be handed in every month seem like an anachronism
that should be replaced by an online form.
• The requirement that GSR appointments must be renewed every three months has
negative implications, including that students cannot have parking fees deducted from
their paychecks.
• The PhD stipend is low. The major problem is rising housing costs. UCLA graduate
housing is steadily increasing prices every year. For example, the cheapest room in
Weyburn Terrace is now $1200/month, which is more than 50% of the stipend (and
after tax, students don’t have much left for food and other expenses).
• We have too few professors in several areas, particularly systems, algorithms, and
programming languages.
• Some professors teach their graduate courses in a way that seems to require more
knowledge than the students expected. The professors should make the prerequisites
explicit such that students can prepare for each course, or be willing to explain or give
resource recommendations when prompted by students.
• The building is in some state of disrepair. Examples are the bathrooms and the many
broken thermostats. A related issue is that the wireless network gets overloaded at
peak times.
• The effort to be a teaching assistant is uneven across courses and ranges from 10 hours
per week to 25 hours per week. Each teaching assistant runs two sessions, though the
distribution of students on those two sessions may be highly uneven. Additionally,
when graders do a poor job, the teaching assistants have even more work to handle
complaints.
27
• The female-male ratio is low across PhD students, though better across MS students.
The number of African American PhD students is small; at the moment we have only
two.
• In the past year we had an insufficient number of spots in our undergraduate courses
for graduate students who need the courses to satisfy the breadth requirement.
• The UCLA-wide computing cluster is inadequate for the systems research that some
students do.
Finally, the students had ten suggestions for improvement:
• Establish a writing seminar, perhaps in the spirit of the course that trains teaching
assistants.
• Establish a small core of required graduate courses.
• Allow alternatives to the current requirement of one major and two minors. An idea
could be one larger major and one minor. A related idea is to allow Statistics as a
minor.
• Require the CS201 summaries to be more substantial and integrate peer review into
the grading process.
• Publicise UCLA’s resources and courses about entrepreneurship.
• Require professors to dedicate some of their office hours to graduate students.
• Encourage professors to attend graduation to congratulate their graduate students.
• Give international students more help with such challenges as housing and visa.
• Establish more mechanisms to enable graduate students to learn what is going on
in other groups in the department. The poster session this spring was a help, and
other ideas include a “lab open house” and a webpage with links to information about
area-specific seminars and reading groups.
• Improve the laboratory in which some graduate students help teach our 35L laboratory
course for undergraduate students. The current laboratory has Windows machines,
while the course focuses on Linux. As a result, each undergraduate student brings a
laptop, which in turn means that to give good help, the teaching assistants need to
understand the environment on each student’s laptop.
PhD student placement. During the period 2006–2014, most of our PhD graduates joined
industry, yet we also placed our PhD students in a variety of academic institutions, both in
the United States and abroad. The following is a list of some of the most prominent academic
institutions in which we placed PhD students as assistant professors (some of whom are now
associate professors).
28
Berkeley
Cornell University
University of Michigan
Johns Hopkins University
Ohio State University
SUNY Stony Brook
University of California, Riverside
SUNY Buffalo
University of Texas at Dallas
We also placed PhD students as assistant professors (or the equivalent) at the following
world-class foreign universities: Fudan (China), KAIST (South Korea), Peking University
(China) and University of Oxford (United Kingdom), and also at these other foreign universities: Ben-Gurion University of The Negev (Israel), Hanyang University (South Korea),
University Federal de Minas Gerais (UFMG, Brazil), University of Information Technology
(Vietnam), University of Southampton (United Kingdom), Xi’an Jiaotong-Liverpool University in Suzhou (China).
We also placed PhD students at these institutions that may have only undergraduate
and MS programs in computer science: Bucknell University, University of Massachusetts
(Boston), California State, Northridge (2).
Further, we placed one PhD student as lecturer at Northeastern University, and one PhD
student as research assistant professor at Rennselaer Polytechnic Institute.
Additionally, we placed PhD students as researchers at the following research laboratories: Adobe Research Lab, Comcast Labs, Disney Research Zurich, Honda Research Institute, IBM T.J. Watson Research Center (6), Jet Propulsion Laboratory, NASA/Caltech,
Microsoft Research India (2), Palo Alto Research Center (PARC), SAP Labs (2), Symantec Research Labs, Technicolor, Paris Research and Innovation Center, USC Institute for
Creative Technologies, USC ISI, VeriSign Labs.
Summary. Overall, we have a strong and vibrant PhD program. The PhD students
are overwhelmingly positive about the program, although they also have suggestions for
improvement. We will continue to make the PhD program even better.
F
Postdoctoral Scholars
In the period 2008–2014, we had 47 post-docs who all played a significant role in our research
mission. The appointments were for one year (31 post-docs), two years (10 post-docs), or
3–5 years (6 post-docs). Faculty supported all 47 post-docs from grants, and none of the
post-docs taught courses. Some post-docs helped mentor students and a few gave guest
lectures in our courses.
All indications are that the post-docs who left have already successfully moved on to
the next stage in their careers. Some are professors at such schools as Ben-Gurion University (Israel), IIT Delhi (India), IMDEA (Spain), KAUST (Saudi Arabia), Oxford (UK),
and USTC (China). Others are in industry positions at large companies such as Amazon,
Google, and Intel, or smaller companies such as Calypto Design Systems, LogicBlox, Scal29
able Network Technologies, and ThousandEyes. Finally, a few have continued in post-doc
positions elsewhere, and one is an officer at the European Patent Authority.
G
Articulated, Concurrent & Self-Supporting Programs
In cooperation with the John E. Anderson Graduate School of Management, the Computer
Science Department offers a concurrent degree program that enables students to obtain the
MS in Computer Science and the MBA (Master of Business Administration). The curriculum
requirement is 80 MBA units, 9 CS courses (at least 5 at graduate level), and CS breadth
and seminar courses. In 2006–2014, a total of two students enrolled in the program.
H
Diversity
The Computer Science Department and its faculty members strive for diversity within the
department’s faculty and student populations. We do this by advertising widely, by engaging
in many outreach activities in order to attract a greater number of women and members
of underrepresented groups to our undergraduate and graduate programs, and by further
providing excellent opportunities once these faculty and students join the department. We
have many events and strive to foster a diverse and inclusive environment, as we discuss
below.
Faculty. The 27 regular faculty consist of 21 white males, 4 Asian males, and 2 Asian
females. We lost two female faculty and hired one female faculty in the past two years.
Before those changes, all of our three female faculty members had endowed chairs.
We are eager to hire new female faculty. In Spring 2014, we interviewed four female
faculty candidates and have so far offered positions to two of them, though both declined.
One of our female faculty members served on the search committee in 2012–2013, and we
plan to ask a female faculty member to serve on the search committee in 2014–2015.
Two years ago, our only Hispanic faculty member retired, and at the moment we have
no Hispanic or African American faculty members. We are eager to hire new faculty from
underrepresented minorities, and we advertise in several advertising outlets that reach diverse
groups, namely:
Society of Women Engineers, http://www.swe.org
National Society of Black Engineers, http://national.nsbe.org
Society of Hispanic Professional Engineers, http://www.shpe.org
Society of Mexican-American Engineers and Scientists, http://www.maes-natl.org
American Indian Science and Engineering Society, http://aises.org
Society for Advancement of Chicanos & Native Americans in Science,
https://sacnas.org
We chose those outlets after discussions with Vice Provost Littleton.
Along with the efforts of the search committee, the department chair pays special attention to faculty applications from women and minorities. Regardless of gender or ethnicity, all
faculty members are expected to meet the same teaching standards and course load, as well
30
as contribute to the welfare of the department by attending faculty meetings, participating
in faculty candidate interviews, serving on committees, etc.
Students. Below is a summary of the Fall 2013 enrollment in our degree programs, with
a focus on the numbers of women and minorities:
CS
CSE
MS
PhD
Total
433 (71 women =
240 (39 women =
143 (26 women =
161 (21 women =
16%, 12 Hispanic =
16%, 16 Hispanic =
18%, 8 Hispanic =
13%, 3 Hispanic =
3%, 2 African American)
7%, 2 African American)
6%, 0 African American)
2%, 2 African American)
In Fall 2013, we had no Native Americans in our degree programs.
These numbers are a strong reminder that we must hire more faculty from underrepresented minorities so that they can serve as role models.
Note that the above number of PhD students stems from a count done at a different time
(Fall 2013) than the June 2013 count that we report in the section on Graduate Programs.
For Fall 2013 and Fall 2014, we have the following numbers of new undergraduate students:
CS
CSE
Total
new
56
59
115
in Fall 2013
(16 women = 29%)
( 9 women = 15%)
(25 women = 22%)
new
52
59
111
in Fall 2014
( 8 women = 15%)
(12 women = 20%)
(20 women = 18%)
For Fall 2014, 691 women (21% of the applicants) applied to CS while 472 women (18% of the
applicants) applied to CSE. Associate Dean Wesel’s office admits undergraduate students
and offered admission to a total of 567 prospective CS and CSE students for Fall 2014.
Among those, 150 are women = 26%. Thus, Dean Dhir’s office does a good job of offering
admission to a higher percentage of women than we currently have. Despite that, the
percentage of women in our undergraduate programs will stay largely unchanged, though
the high percentage of female CS freshmen in Fall 2013 was a big positive and is grounds for
optimism.
Our department admits graduate students after approval by the Graduate Division. We
offered admission to 268 MS students and 46 PhD students for Fall 2014. Among those, 81
MS admits are women (30% admission rate), and 18 PhD admits are women (39% admission
rate). Eventually, a total of 53 women accepted MS admission (65% yield), and a total of 2
women accepted PhD admission (11% yield).
In the future, we will strive to offer admission to a higher percentage of female MS
students. The admission of MS students is done by a department-wide committee. In
contrast, admission of PhD students is done by a combination of individual faculty members
and a committee that sets a department-wide bar. We can try to reach a target for admission
of female MS students, while if we set a target for admission of female PhD students, it would
intrude on each faculty member’s privilege to select their own PhD students. We encourage
faculty members to carefully consider female PhD students and we leave it at that.
Outreach. We are working with the UCLA Graduate School of Education & Information
Studies and the Los Angeles Unified School District (LAUSD) to increase the number of
31
women and underrepresented students in computer science. For example, as part of the AP
readiness program, LAUSD students (predominantly from underrepresented groups) and
teachers participate in weekend AP computer science enrichment sessions at UCLA.
In Spring 2014, students from UCLA’s ACM chapter have visited nine local high schools
to spread the word about UCLA and to interest students in an education and a career in
computer science.
Computer Science Department. We have supported a number of women and underrepresented graduate students under the DOE-sponsored GAANN fellowship program and the
National GEM Consortium.
Several of the Department’s research centers have received funding for programs and
partnerships that focus on increasing diversity in the field of computer science. For example,
the Center for Domain-Specific Computing has an educational component with an emphasis on attracting underrepresented students at all levels through partnerships with campus
organizations focused on diversity. Similarly the Center for Embedded Networked Sensing (2002–2013) hosted many undergraduates and high school students in summer research
internships, including many women and members of underrepresented groups.
UCLA Engineering. Faculty members Alfonso Cardenas and David Smallberg co-led the
NSF-funded FOCUS program (Frontier Opportunities in Computing for Underrepresented
Students) in collaboration with the School’s Center for Excellence in Engineering and Diversity (CEED). The goal was to increase the participation, retention, and performance of
underrepresented minority students pursuing baccalaureate degrees in computing disciplines.
FOCUS encouraged and fostered current and potential community college underrepresented
transfer students through summer courses, bridge programs, school-year seminars, and support programs. NSF funding for this program concluded in 2013.
CEED is committed to the development, recruitment, retention, and graduation of underrepresented engineering and computing students. Its support includes an intensive Computing Immersion Summer Experience to better prepare incoming underrepresented freshmen
and transfer students for university-level computer science courses and to expose them to
research and industry. It supports student chapters of the American Indian Science and
Engineering Society, the National Society of Black Engineers, and the Society of Latino
Engineers and Scientists.
Social events. Our department has annual faculty-oriented social events that have been
successful in bringing almost all of the faculty together. In particular, we have an annual fall
social in a faculty member’s home. Additionally, we have a history of events that celebrate
major awards and major birthdays. For example, we had one-day events to celebrate Judea
Pearl’s 2011 Turing award and a major birthday of Leonard Kleinrock in 2014. We are
fortunate that both current and emeriti faculty attend such events.
During the two years of 2010–2012, one of our female faculty members hosted periodic
meetings and dinners (funded by the CS department) for female undergraduate students,
graduate students, post-docs, and faculty members. Those events were reportedly successful
in fostering camaraderie and mutual support among the women in our department. In UCLA
Engineering, we have the Society of Women Engineers (SWE), which is a major positive
force for our female students. The department chair has asked many female undergraduate
students about possible interest in starting a Women in Computer Science group, and the
consistent answer has been that SWE is sufficient.
32
Our two main social events for the entire department are our spring and fall picnics.
Those picnics are successful for bringing together a diverse group of undergraduate students,
graduate students, post-docs, and faculty.
We have events that are intended mostly for graduate students, post-docs, and faculty.
First, we have department-wide seminars twice a week, and we serve food and drinks before
each event. Each event successfully brings people together informally for 15–20 minutes
before the talk begins. Once a week we have tea-time for an hour where the objective is
purely social, although we occasionally hear a five-minute pitch by a company. (Usually those
tea-times are sponsored by companies, and we serve food as well as tea.) Third, we have an
annual holiday lunch for graduate students, post-docs, faculty, and staff. Those lunches are
the most ambitious of all our events, and they bring together people from our department
and also a few friends of the department, such as staff members in other departments.
Grace Hopper. Starting in 2014, our department will sponsor female students to attend
the annual Grace Hopper Celebration of Women in Computing. Six female undergraduate
students will attend in October 2014.
Overall, we want to heighten the awareness that our department is an inclusive environment that is welcoming and accommodating to women and minorities.
I
Comparison to the Previous Review
These are some key numbers that show how our department now compares to the department
at the time of the previous review:
2006
2014
Faculty FTE
36
29
Graduate students
329
346
Undergraduate students
540
673
Research expenditure
$7.6M $10.9M
U.S. News ranking
15–17
13–14
Dean’s
target
38.5
380
700
N/A
top-10
The previous review concluded with a Summary of Recommendations that was divided
into three categories: recommendations to the Dean, recommendations to the Dean, Chair,
and Department, and recommendations to the Chair and Department. Additionally, the
main body of the previous review contained other recommendations. We will now discuss
improvements since 2006 in response to those recommendations, except those directed to the
Dean.
Recommendations to the Dean, Chair, and Department
1. Additional and equitable funding for graduate student support should be obtained from
outside agencies (federal, private sector) in an attempt to maintain three years of guaranteed
support. If adequate funding for graduate students cannot be generated, it may be necessary
to reduce enrollments.
33
We have made major progress. We have increased our research expenditures from $7.6
million in 2005–06 to $10.9 million in 2012–13, and our goal is to increase the funding
guarantee for all PhD students from two years to three years, possibly starting in 2015.
2. The Department should aggressively pursue funding in order to create endowed chairs
(ideally at least two more). These positions will be essential for recruiting and retention.
Done! Thanks to Dean Dhir, we have two new chairs, namely the Symantec Chair and
the Kleinrock Chair. Additionally, Jason Cong and Demetri Terzopoulos are Chancellor’s
Professors. Finally, we continue to have the two Postel Chairs, the Friedman Chair, and the
Samueli Fellowship.
Recommendations to the Chair and Department
1. The Department should dissolve its division into the eight different research areas. In
its place, the Department should form an elected executive committee that may be comprised
of members with differing research interests. This committee will function in advising the
chair in making department-wide decisions.
We have made progress. The department has a Policy and Planning Committee that
consists of former department chairs and serves the purpose of an executive committee.
Additionally, we formed ten other standing committees (on academic policy, awards, bylaw-55, MS admission, PhD visit day, PhD admission, PhD progress tracking, policy and
planning, recruiting, and written qualifying exam), and we have several ad hoc committees
each year. While we continue to divide the department into eight areas, those areas now
serve only three purposes that are all administrative: 1) certification of breadth requirements
and plans of study for the graduate program, 2) documentation of course improvements in
the context of ABET and CSAB, and 3) coordination of the teaching of related courses in a
given school year.
2. The Department should create a graduate student handbook. This and other detailed
graduate student requirements, should be consolidated in one location such as the departmental web site.
Done! See http://www.cs.ucla.edu/academics/graduate-program.
3. The Department should follow through on its plan to adequately track the progress of
graduate students. Annual progress meetings with graduate students should be documented.
Done! We have an annual process that begins with contacts between our PhD progress
tracking committee, the PhD students and their advisors, continues with a faculty meeting
at which we discuss every student, and culminates with sending a progress letter to each
student.
4. The Department should become actively engaged in outreach activities in order to
attract a greater number of women and members of underrepresented groups into the undergraduate major and the graduate program. In this regard, the Department should actively
engage and seek assistance from graduate division and from the CEEDs office in the School of
Engineering, which has programs designed to increase minority enrollments in the School (i.e.
Step-Up partnership program with the Cal. State. system). In order to increase the recruitment and retention of underrepresented minority students, we suggest that the Department
also tap the expertise available on campus offered by Academic Advancement Program (AAP)
and the Student Retention Center (SRC).
34
Done! We have many outreach activities that target women and members of underrepresented groups, as described in the section on diversity.
5. In order to make working with junior faculty more attractive to graduate students, the
Department should create a larger general pool of funds for the funding of first-year students.
This will also protect the junior faculty from having to make multi-year commitments to
graduate students, sight unseen.
Done! For example, in 2012–13, we assigned 65% of the department’s funding for graduate students (which totals $1,643k) to first-year graduate students. We spent most of the
remaining funds on teaching assistants who are in their second year or later. None of our
teaching assistants are first-year students.
6. The sense of community among graduate students is poor, in part due to the separation
into labs, and in part due to the realities of life in Los Angeles. The Department should look
for creative ways to improve camaraderie (the recent innovation of faculty-student basketball
games is a nice idea, but is inevitably narrow).
We have made major progress. In response to the previous review, the graduate students
formed the Computer Science Graduate Student Council (CSGSC) that serves some of the
needs of our graduate students by organizing social events and bringing forward requests
to the department. Their signature event series is the weekly Wednesday Tea Time, which
large numbers of graduate students and faculty attend. The CSGSC plays a major role in
planning and running the visit day for prospective PhD students, and organizing orientation
events for new students. The CSGSC leaders are in frequent contact with the department
chair. All indications are that the CSGSC has helped improve the sense of community
among our graduate students. Additionally, we started to assign every new PhD student
to an advisor from day one. The students of that advisor form a group from which the
new student can seek advice, etc. We also created a graduate student lounge for interaction
among graduate students. Finally, our new large research efforts have helped increase the
research interactions among students.
Other Recommendations
We will comment on six recommendations that were made in the main body of the previous
review.
Faculty growth. The previous review contained a recommendation from the external
reviewers of “a net gain of at least five faculty,” which at the time would mean a growth
from 37 to at least 42. Dean Dhir’s current target for our department is 38.5. Since 2006 we
did hire some faculty, but also lost faculty due to retirement, denial of tenure, and faculty
moves. We currently have 29 FTE including 2 permanent lecturers, plus 1 new hire who will
join the department some time between summer 2014 and summer 2015. We believe that
our current momentum in hiring can bring us close to 38.5 FTE within two years, and we
agree with the previous review that more FTEs are needed to get back into the top-10.
Additional fund manager. The previous review recommended that “at least one more
fund manager is required.” In his memo of Dec 13, 2013, Dean Dhir promised a future
increase of our staff budget from 15.65 FTE to 16 FTE. The increase appears to be sufficient
to hire a part-time fund manager.
35
Faculty advising. The previous review recommended that “more systematic/uniform
undergraduate advising should be an immediate goal.” Thanks to Associate Dean Wesel,
we now have systematic faculty advising of undergraduate students. Every faculty member
meets with about 30 undergraduate students for three hours every quarter to talk about
anything—from graduate school, where to go for an internship, disappointing classes, or
anything else that may be on the students’ minds. The students are required to attend one
of those meetings every year. In practice, about 10 show up for any given meeting, which
is small enough to make it an enjoyable and productive experience for all. Associate Dean
Wesel’s office started these meetings in 2008, and the response has been overwhelmingly
positive.
Written qualifying exam. The previous review mentioned “significant dissatisfaction with
the written qualifying exam.” In response, we completely changed the written qualifying
exam. The new exam requires students to write “a high-quality paper, solely authored by
the student. This can be either a research paper containing an original contribution, or a
focused critical survey paper.” The new exam encourages students to engage in research
soon after they enter our PhD program.
Better orientation. The previous review recommended that we improve the orientation of
incoming students such that they “have a better idea of what they’ve signed up for.” UCLA
Engineering has an Open House for prospective undergraduate students. Our orientation
session during the Open House emphasizes that the first-year courses are rigorous yet doable.
Honors thesis. The previous review mentioned that “students also recommended the
institution of a senior honors thesis option.” We have experimented with such an option
and eventually settled on a system where students can get credit for research, yet without
calling the effort a senior honors thesis.
Additional Improvements
We will discuss five additional improvements that we have made since the previous review.
Increased PhD stipend. We significantly increased the stipend for PhD students such
that it matches that of Berkeley. After the increase, we saw an immediate jump in the yield
of new PhD students.
Prerequisites. We added prerequisites to several undergraduate courses. The prerequisites
lead to improved sequencing of courses, which in turn gives us more predictability and fewer
scheduling headaches.
Department bank. In 2013 we started a department “bank” for “depositing” external
funding that otherwise would go back to the sponsor. A deposit is done by supporting, as a
GSR, a 1st-year PhD student that the department is obligated to support. The professor who
makes the deposit must certify effort reporting for that student, indicating that the student
worked on the grant that was used to support him or her. A withdrawal is accomplished
by the department supporting any graduate student chosen by the faculty member who
made the deposit. In the first year of operation, faculty members deposited a total of $100
thousand.
ACM Programming Contest. We will send two undergraduate students to St. Petersburg,
Russia, in June 2014 for a week-long course on how to do well in the ACM Intercollegiate
Programming Contest. The course is taught by current and former coaches and members
36
of winning teams from St. Petersburg. Thanks to Vice Provost Atchison, we invited the
teachers of the course to give the course at UCLA in Fall 2014. We hope these efforts will
take us on a path back to our performance level of the 1980s, when we won the finals in 1989
after seven other top-10 finishes.
Healthier food. We introduced healthier food options at the twice-a-week departmentwide seminars.
J
Resources
We follow the Senate guidelines and address resources in Appendix N.
K
Goals and Plans
Our long-term goal is to enter the top-10 among computer science departments in the United
States; we are currently number 13–14 according to U.S. News & World Report.
As an overarching point, we emphasize that the huge interest in our undergraduate
programs is an opportunity for UCLA. The number of applications to our undergraduate
programs has increased dramatically; however, the size of our undergraduate program has
increased only modestly.
applicants
offered admission
joined UCLA
for Fall 2005 for Fall 2014
1434
5994
21%
9%
84
111
The tremendous interest in computer science is an opportunity for UCLA: admit more undergraduate students to our programs and grow the faculty size correspondingly. Our hope
is that UCLA will create a task force with the goal to determine the appropriate size for a
top-10 computer science department.
In this remainder of this section we will explain our six short-term goals that will be
steps towards a better ranking. Those goals concern the hiring of faculty, the emerging
area of big data, the PhD program, the placement of PhD students, the MS program, and
the undergraduate programs. Briefly, our short-term academic goals are to hire seven new
faculty members (we have permission), to enhance research and teaching in the emerging
area of big data, to increase the funding guarantee for all PhD students from two years to
three years, possibly starting in 2015, to improve our placement record, to create a courseonly option in the MS program, and to continue to improve our undergraduate courses as
required by ABET and CSAB.
Hire Seven New Faculty Members
The number of faculty dropped from 36 FTE eight years ago to now 29 FTE. In response,
we received permission to hire eight new faculty members in 2013–2016, and we have been
interviewing and extending offers vigorously. We have hired one, so we have seven to go.
37
Once we have hired seven more, our faculty size will be 37 FTE. However, in 2014–2016 we
also anticipate at least one retirement, so we will seek permission to hire additional faculty
after 2016, within Dean Dhir’s target for our department of 38.5 faculty.
Enhance Research and Teaching in the Emerging Area of Big Data
Three of our four most recent hires are Tyson Condie, Ameet Talwalkar, and Wei Wang,
who all focus on aspects of the emerging area of big data. These faculty enhance our existing
strength and we plan to add another one or two faculty members to the area. We have formed
the Scalable Analytics Institute as a center for research on big data and we plan to enhance
our list of courses in the area. In Section D we described how we successfully responded
to the big shift towards parallel, concurrent, and distributed computing by adapting our
programs and individual courses. We are in the process of responding similarly to the big
shift towards big data technology that is taking place this decade. Our plan is to have critical
mass of faculty, research efforts, and courses such that students interested in big data will
see UCLA as a natural place to reach their education goals.
Increase the Funding Guarantee for All our PhD Students
Since 2011, we have guaranteed two years of support to every incoming PhD student, unless
he/she already has support from an outside agency. One of the positive effects is that
we no longer have a waiting list of PhD students who need to be a teaching assistant to
have funding. Rather, for the first time in many years, we have started offering teaching
assistantships to our MS students and even graduate students from other departments.
Here is a calculation that shows that we indeed have the funding needed for all our PhD
students, or we are close. First we calculate the amount of funding, including indirect cost,
needed to fund 190 PhD students. We work with the number 190 as our estimate of the
average number of PhD students across any given year (students may graduate after any
quarter). For simplicity, let us divide our students into four groups:
stipend # students Cost (in $)
Domestic, CA resident 9 months $47,183
62
2,925,346
Domestic, CA resident 12 months $58,350
27
1,575,450
International 9 months $62,285
71
4,422,235
International 12 months $73,452
30
2,203,560
Total
190 11,126,591
The column labeled # students is based on the observations that in June 2014, 53% of
our PhD students are foreign and that in summer 2013, 70% of our PhD students went on
summer internships. Next we calculate how much funding we have available. Our research
expenditure in 2012–13 was $10.9 million, including indirect cost. Additionally our department has $1,643 thousand available in instructional support for graduate students, which, if
we add indirect cost, would correspond to $2.5 million. (We prefer to work only with numbers that include indirect cost to ensure that we compare “apples to apples.”) The faculty
spend some of the research funding on summer salary, which, if all regular faculty receive
three months of summer salary, totals $2.1 million, including indirect cost. For simplicity,
38
let us ignore other ways to spend research funding and estimate that the funding available
is:
Research expenditure $10.9 million
+ Instructional support $2.5 million
−
Summer salary $2.1 million
Total available $11.3 million
In summary, we need $11.1 million to fund all our PhD students, and we have close to
$11.3 million available. Looks good! Even better is that some of our PhD students have
funding from outside agencies and some are GSRs in other departments, so those students
don’t require funding from our department. On the side of caution, we should remember
that stipends will go up by 3% in summer 2014, and that we may decide to increase the
support from Step 7 to Step 8 (which would be an 8% salary increase). Overall, we conclude
that either we have sufficient funding to fund all our PhD students, or we are close. So,
our goal is to increase the funding guarantee for all PhD students from two years to three
years, possibly starting in 2015. We will use the rest of 2014 to work out a detailed plan
and then hopefully guarantee three years of support starting in Fall 2015. After a few years
of experience with the guarantee of three years of support, we will evaluate the results and
consider whether we should go further and guarantee four or more years of support.
Improve our Placement Record
The analysis in Section B shows that our placement record is considerably weaker than those
of the ten schools with the best placement records. We plan to improve the preparation of our
top PhD students for an academic career. In particular we will do more to ensure that our
faculty promote our students when opportunity presents itself, that the students are ready
for the interview process, and that the students have experience with writing proposals for
funding.
Additionally, we will do more to improve the quality of the incoming PhD students.
For example, two years ago we started a 3+2 program with Peking University that enables
students University to spend three years at Peking University and two years at UCLA. Each
student will receive an undergraduate degree from Peking University and an MS degree from
UCLA. Our objective is to convince some of those students to pursue a PhD at UCLA.
Our long-term experience is that students from Peking University are often among the best
students who enter our PhD program. We believe that the 3+2 program can help us to get
more top-quality PhD students which eventually should help us improve the quality of our
PhD graduates.
Hopefully those efforts will help improve our placement record.
Create a Course-only Option in the MS Program
Our number of MS students has grown from 91 in 2004–2005 to 165 in 2012–2013. As
discussed in Section E, we plan to continue to have 165 MS students. Encouraged by Dean
Dhir, in Spring 2014 we started to explore the possibility of a course-only option in the MS
39
program. Such an option would enable us to advise fewer MS projects and instead spend
more time on our PhD students.
One of the effects of the increasing number of MS students is that many of our graduate
courses are much larger now compared to 2004–2005. A course-only option in the MS
program will further increase that effect. Starting in Fall 2014, UCLA allows our graduate
courses to have teaching assistants. We have applied for resources to have teaching assistants
for the largest of our graduate courses.
Continue to improve our Undergraduate Courses
As discussed in Section D, we have a process of annual evaluation of our course offerings
that leads to written suggestions for improvement. We use those suggestions in future course
offerings and eventually evaluate how well they worked. We will continue this process and
acknowledge that it works well. A little bit of improvement every year sums up to a big
improvement over time.
L
Special Circumstances
Some of the computer science faculty members contribute to the following interdepartmental
degree programs:
• The Computational and Systems Biology Undergraduate Interdepartmental Program.
The major in Computational and Systems Biology is designed primarily for highly
motivated undergraduates interested in interdisciplinary activities in life sciences, behavioral sciences, and the computational, control, communication and information
branches of engineering and computer science.
• The Undergraduate Bioinformatics Minor. The Bioinformatics minor introduces undergraduate students to the emerging interdisciplinary field of bioinformatics, an active
area of research at UCLA combining elements of the computational sciences with the
biological sciences.
M
Conclusion
The National Research Council and Microsoft Academic Search rank our department in the
top-10 based on program characteristics and citations, while U.S. News & World Report
ranks us 13–14 based on our reputation. Our department has a strong momentum with
many highly productive superstars, steadily increasing research expenditures, and a goal to
increase the funding guarantee for all PhD students from two years to three years.
The number of applicants for our undergraduate programs has increased by a factor of
four over the past nine years, and as a result our admission rate was 9% for Fall 2014.
Some of this interest in computer science stems from the large potential for a high-paying
job. The U.S. Department of Labor Statistics discussed employment projections in their
December 2013 monthly labor review, http://www.bls.gov/opub/mlr/2013. The DLS
40
projects that total employment in the U.S. economy will grow by 15.6 million during the
2012-2022 decade, including 685,800 jobs (4.4% of the total job growth) in computer and
mathematical occupations. For comparison, the DLS expects engineering occupations to
add a total of only 136,500 jobs in the same period. The DLS also reported that “the
median annual wage for computer and mathematical occupations in May 2012 was $76,270,
more than twice the median annual wage for all wage and salary workers of $34,750 and
the second highest of any major occupational group.” (Management occupations have the
highest median salary.)
Most of the top-10 computer science departments have grown to meet the high nationwide
demand for an education in computer science. The public schools in the top-10 have numbers
of faculty that range from 49 to 96, which is significantly larger than Dean Dhir’s target of
38.5 FTE for our department. Our small size is the biggest obstacle to achieve a top-10
ranking in U.S. News & World Report.
Computing is an enabling technology for most aspects of modern life, and Jeanette Wing
(former head of computer science at CMU, now head of Microsoft Research International)
wrote in 2006 that “computational thinking is a fundamental skill for everyone,’ https:
//www.cs.cmu.edu/afs/cs/usr/wing/www/publications/Wing06.pdf. In 2006 an expert
panel wrote in their “Towards 2020 Science” report that “Scientists will need to be completely
computationally and mathematically literate, and by 2020, it will simply not be possible to do
science without such literacy,” http://research.microsoft.com/towards2020science/
downloads/T2020S\_Report.pdf. Our faculty are increasingly engaged in many interdisciplinary research efforts across UCLA. A strong computer science department is a major
resource for all of UCLA, and the potential for local impact extends to Silicon Beach, which
is the Santa Monica area that is home to over 500 startup companies and many accelerators
devoted to information technology. UCLA is perfectly located to interact with this emerging source of jobs and wealth in Los Angeles and can do so most effectively with a strong
computer science department.
The tremendous interest in computer science is an opportunity for UCLA: admit more
undergraduate students to our programs and grow the faculty size correspondingly. All signs
are that we are past the period of many retirements, departures, and denials of tenure. We
have hired four new faculty in the past four years, and we will continue to hire vigorously
to get close to 38.5 FTE within the next two years. Our hope is that UCLA will create
a task force with the goal to determine the appropriate size for a top-10 computer science
department.
41
Appendices
N
Resources
We use the template that the Academic Senate Council has approved. This appendix is
self-contained and includes copies of some text and tables from Sections A–M.
Academic Goals
Our long-term goal is to enter the top-10 among computer science departments in the United
States; we are currently number 13–14 according to U.S. News & World Report. Our shortterm academic goals are to hire seven new faculty members (we have permission), to enhance
research and teaching in the emerging area of big data, to increase the funding guarantee
for all PhD students from two years to three years, possibly starting in 2015, to improve
our placement record, to create a course-only option in the MS program, and to continue
to improve our undergraduate courses as required by ABET and CSAB. Our eight research
fields are the same as those of the previous review and all eight fields remain vibrant.
Funding
We list our operational budget, endowment, instructional support, and research funding.
Operational Budget. For 2012–13, excluding faculty and staff salaries and benefits, we
had the following support for department operating expenses:
Source
Contracts and grants
Summer session
Industrial affiliates
UCLA Engineering
Overhead return
Total
Amount (in $)
143 thousand
103 thousand
69 thousand
43 thousand
28 thousand
386 thousand
In this table, the line labeled “Grants and contracts” is funding for the department-wide
computing facilities that is generated from research contracts and grants. In 2012–13 that
amount was $143 thousand.
In Spring 2014, the department had twelve industrial affiliates: Bally Technologies, Blizzard, Cisco, Goldman Sachs, Google, IBM, Mentor Graphics, Northrop Grumman, Qualcomm, Symantec, Teradata, and ViaSat. Each company donates $10,000 every year, which
we split between the department (2/3) and the faculty liaison (1/3). In 2012–13, the department’s share was $69 thousand.
Endowment. The department has a quasi-endowment of $1.3 million.
Instructional Support. Our department received the following instructional support in
2012–13:
42
Source
Amount (in $)
Fellowships
Graduate Division
874 thousand
Teaching assistantships
Graduate Division
418 thousand
Dean’s fellowships
UCLA Engineering
260 thousand
Dean’s nonresident tuition UCLA Engineering
91 thousand
Temporary lecturers
UCLA Engineering
100 thousand
Readers
UCLA Engineering
10 thousand
Special readers
UCLA Engineering
5 thousand
Total
all sources
1,758 thousand
Dean Dhir’s office manages a long list of scholarships, some of which help support our
students.
Research Funding. Our research expenditures are growing:
Year Expenditures (in $)
2012–13
10.9 million
2011–12
10.1 million
...
2005–06
7.6 million
2004–05
7.5 million
Those numbers exclude CENS, an NSF center (2002–2013) led by Deborah Estrin.
In 2012–2013, the average research expenditure per faculty was $389 thousand. According
to the 2012 Taulbee Survey, our average is near the 90th percentile in the United States across
computer science departments with 20–35 faculty at public universities. Our expenditures
were uneven across faculty in 2012–13:
# Faculty
Expenditures (in $)
3 more than 700 thousand
10
300–700 thousand
3
100–300 thousand
5
10–100 thousand
7
less than 10 thousand
Faculty Distribution
Currently we have 27 regular faculty and 2 lecturers with security of employment. Dean
Dhir has set a target for our department of 38.5 faculty. We currently have permission to
hire 8 faculty in 2014–2016, which would bring us to a total of 27+2+8=37, which is close
to our target. However, in 2014–2016 we also anticipate at least one retirement, so even if
we do hire 8 faculty in 2014–2016, we will have room to grow by 2.5 faculty after 2016.
At the time of the last review, we had 34 regular faculty and 2 lecturers with security of
employment. We hired 5 professors since the last review, but we lost even more, for a net
loss of seven. In particular, six retired, two were denied tenure, and four left for positions
at Harvard University, Cornell Tech, Max Planck Institute, and Microsoft Research. We are
now optimistic that we can regain our size.
43
Our recruiting efforts in 2011–2014 have included 49 interviews, 27 offers, and 4 hires,
while we have 2 outstanding offers at the moment. The 21 people who declined our offers
joined MIT, Stanford, Berkeley, CMU (2 people), U. Washington (2 people), Georgia Tech,
Columbia (3 people), U. Michigan, U. Chicago, EPFL (2 people), ETZ Zurich, Microsoft (3
people), and Google, while one stayed as a professor at Brown University. The list shows
that we are competing with the top schools and research labs.
A major challenge is that most universities have significantly expanded the number of
faculty in their computer science departments over the past decade and continue to hire
many professors. We experience routinely that our candidates receive multiple offers from
top-10 schools, and the above list shows that many of them do join one of those top-10
schools. We fiercely avoid to interview second-tier researchers, and as a result we are always
in competition with the top schools. In the past decade, many of our hires happened because
the candidates had personal circumstances that made them prefer life in Los Angeles.
Another major challenge is that faculty salaries for incoming professors rose rapidly in
computer science across the United States in 2011–2014. For example, one candidate who
was within four years after PhD received an offer with an academic year salary as assistant
professor of $135,000 from a top-10 university in the United States. Another candidate
who was within six years after PhD received a tenured offer with an academic year salary
as associate professor of $140,000 from a well-ranked university in the United States. We
cannot compete with such salaries.
Dean Dhir has set the following student enrollment targets for our department:
380 graduate students
700 undergraduate students
Our numbers of students are currently fairly close to those targets, and once we hire new
faculty, our class sizes will get closer to comfortable levels.
The 27 regular faculty consist of 21 full professors, 4 associate professors, and 2 assistant
professors. We want to hire mainly assistant and associate professors in the next few years.
Our faculty are distributed across eight research fields:
Field
Architecture
Artificial Intelligence
Computational and Systems Biology
Graphics and Vision
Information and Data Management
Networking
Software Systems
Theory
# Faculty
6
3
2
2
5
3
2
4
Some of our planned hiring is to bring some of the fields up to critical mass, while other
hiring is to gain strength in the emerging area of big data. Big data draws from a variety of
existing disciplines, particularly artificial intelligence and information and data management.
44
Staff Support
Our department has 14 permanent staff members and 6 temporary work-study helpers, while
individual professors have a total of 5 assistants, funded by grants and contracts. The 14
permanent positions are:
• Management Services Officer: Responsible for the day-to-day operation of the department. The MSO is directly responsible for or assists the department chair in planning,
organizing, staffing, and directing the teaching, research, administration, and public
activities of the department. Additionally, the MSO serves as a backup person for all
staff positions in the department.
• Fund Manager: Responsible for managing all contract and grant activities for preand post-award administration including: budget preparation, adhering to UCLA and
sponsor submission requirements, fiscal oversight, and closeouts. The fund manager
provides analysis and guidance regarding University contract and grant policies, procedures, and practices.
• Purchasing: Responsible for processing all incoming invoices, placing purchase orders,
and processing travel reimbursements. Assists students, faculty, and staff with access
to labs and facilitates resolution of issues regarding parking access. Supports the
funding manager in post-award administration, processes monthly network changes,
and creates budget reports and projections for faculty. Oversees the completion of
reports in the Effort Reporting System.
• Staff Payroll/Personnel: Responsible for all payroll and personnel functions of the
department. Processes appointments for staff, work-study, reader, graduate student
researcher, teaching assistant, visiting scholar, and postdoctoral scholar appointments;
monitors and posts vacation and sick leave accruals and use, and posts all salary-related
expense transfers as requested.
• Academic Personnel: Responsible for all academic payroll and personnel actions, merits, promotions, and new appointments. Maintains and updates the dossier database
and prepares reports and memos on demand.
• Graduate Student Affairs (two people): Responsible for graduate student academic affairs and graduate student admissions, especially of all university and departmental
procedures, and processing of all related documents. Maintain the student database
and files, manage student funding, assign teaching assistantships, and coordinate selection procedures for university, department, and external agency awards.
• Undergraduate Students Affairs: Responsible for assisting with the department’s undergraduate students, groups, and programs, in addition to the administration of class
scheduling.
• Chair Assistant: Responsible for assisting the department chair with meetings, committees, presentations, and correspondence. Also, coordinates recruitment, affiliate
agreements, the Jon Postel Lecture series, conference room reservations, and department events.
45
• Administrative Assistant: Responsible for assisting the 4th-floor faculty with classrelated issues, CS201 seminars, department website, visa processing, travel arrangements, reimbursements for faculty and students, graduate student lockers, audio visual
requests, submission of technical reports, visiting graduate and undergraduate students, and copiers.
• Administrative Assistant: Responsible for assisting the 3rd-floor faculty with classrelated issues, space database, evaluations, visa processing, audio visual requests and
copiers. The individual also processes travel arrangements, check requests, and reimbursements for faculty and students.
• Computing Facilities Staff (three people): Responsible for the installation, maintenance, and upgrading of the departmental computer systems and infrastructure, including networking, hardware, and systems administration; also responsible for electronic mail, computation and data storage, backups, and security services, along with
a general help service for the department’s faculty and staff. Maintain the databases
of graduate students and technical reports, and run the software that supports the
Ph.D. Written Qualifying Exam. While SEASnet also provides help services, the close
availability of our own staff has proven immensely useful for quickly handling problems
and helping users work with new systems.
The table below shows the 2014 count of faculty and staff in the three largest departments
in UCLA Engineering:
Department
Electrical Engineering
Mechanical and Aerospace Engineering
Computer Science
# Faculty FTE
45
30
29
# Staff
21
15
14
This table shows that the faculty-to-staff ratios are similar across the three departments.
Our staff is adequate for our current needs, yet once we hire 9.5 faculty FTE to reach Dean
Dhir’s target of 38.5, we will need additional staff support.
Graduate Student Support
In 2012–13, the Graduate Division and UCLA Engineering gave us a total of $1,643 thousand
for support of graduate students. In 2012–13, we had research expenditures of $10.9 million,
the bulk of which went to support PhD students.
In June 2013, we funded our 181 PhD students from the following sources:
46
TA
GSR
no support
unknown
GSR other department
graduate division
external agency
UCLA Engineering
TA other department
development
28%
27%
12%
8%
7%
6%
5%
4%
2%
1%
This table shows that most of our students are funded, yet we strive to fund all our PhD
students. Since 2011, we have guaranteed two years of support to every incoming PhD
student, unless he/she already has support from an outside agency.
Our senior exit survey indicates that a total of 26.7% of our undergraduate students
participated in research in 2011–12, but only 13.0% in 2012–13. Both numbers have large
error margins, yet suggest that we should do more to achieve our goal of a steady 25%
participation rate. The undergraduate students who participate in research usually get
course credit rather than financial support.
Student Enrollment
Our student numbers have increased significantly since the last review, while our number of
faculty has decreased; this has resulted in large class sizes.
2004–2005
PhD students
196
MS students
91
undergraduate students
540
faculty FTE
36
graduate student to faculty ratio
8
2012–2013 target
181 215
165 165
718 700
29
38.5
12
10
The column labeled “target” shows the targets that Dean Dhir set for our department. The
target for the total number of graduate students is 380; we divided that number into 215
PhD students and 165 MS students. Our students numbers are close to the targets.
Physical Resources
In this section we describe our physical resources, particularly our space, network, computers,
and teaching laboratories. Those resources are adequate for our needs.
Space. Our department occupies most of the 3rd and 4th floors of Boelter Hall, plus the
CENS building next to Boelter Hall. That space includes offices for faculty, students, and
staff, laboratory space for teaching and student research, and rooms for computing facilities
and other utilities. Some aspects of the building need repair, including the restrooms and
thermostats. Once we fill the vacant faculty slots, our space will be fully utilized.
47
We anticipate that in 2018 much of the department will move into a new building (Engineering 6), while the teaching laboratories, the computing facilities and the associated staff,
and some faculty and their students will stay in Boelter Hall and the CENS building.
In 2014 Dean Dhir asked for and got four of our faculty offices for use by faculty from other
UCLA Engineering departments. This was precipitated by a space shortage in Engineering
and can be seen as an early step in the move of much of our department to the new building.
Networking Infrastructure. The department network is built with Cisco Systems hardware
based on the 6500 series switches/routers. Available throughout our space are 1100 switched
10/100MB ports and 192 switched 1000MB ports. The network has redundant Cisco firewalls
and border routers which connect to the campus gigabit backbone. Every room is wired
with a category 5 twisted pair cable with a minimum of 4 connections for small offices
and as many as 32 connections in medium-sized labs. Available throughout our space is
a 300MB wireless network (802.11n). The wireless network is controlled/monitored by a
Cisco/Forescout authentication system.
To date, both the wired and wireless networks have proved sufficient for the department’s
needs. We have observed no significant or persistent problems due to lack of bandwidth on
either network. The security system, augmented by various software tools and careful monitoring by the facility’s staff, has also proved suitable to the challenges of our environment.
We have had no major security incidents for several years, and we have quickly caught and
remedied occasional single-machine infections by viruses or worms.
The networking infrastructure is near the end of its useful life and we plan a major
upgrade in 2014. The current networking infrastructure was installed around 2002 with
the generous support of Cisco (a cost of approximately $500,000) and has received minor
upgrades annually.
Computing Infrastructure. Our server infrastructure is comprised mostly of Sun MicroSystems hardware and software (Solaris) that are housed in a special machine room
controlled and administered by our facility staff:
SunFire 280R x 4
SunFire x4200 x 3
SunFire T1000 x 3
SunFire V40z x 2
SunFire X4500 x 1
SunFire X2100 x 1
Dell PowerEdge 860 x 2
Dell PowerEdge 2950 x 1
Supermicro Servers (various) x 10
Apple MacMini Servers x 4
The Computer Science Department, with its varied individual research groups, also operates
and supports hundreds of workstations. Intel, Dell, Apple, and Sun Microsystems are among
the most prominent vendors of the workstations. These systems are all connected by the
department’s network to the campus backbone. Various research groups also have specialized
equipment of various sorts targeted toward their particular needs. Most of these machines
are also connected to the campus backbone through the department’s network. Some of
the server machines and pieces of special hardware are housed in the facility machine room.
Others are stored in the research areas of their own groups. The department facility generally
takes a more active role in managing the machines in the facility machine room than those
stored elsewhere.
Teaching Laboratories. We have the following four teaching laboratories.
48
• Graduate Workstation Room. This lab is set up for graduate-level class use and for
drop-in use by our graduate students, who all have full access to the equipment. The
equipment includes:
10 Dell PCs running Windows
10 Dell PCs running various flavors of Linux
6 MacIntosh’s running Mac OS X
2 HP 9050dn printers
1 HP scanner
Many graduate students access other computing facilities in their own research groups.
Both the type and amount of equipment in our graduate workstation room have proven
adequate for the needs of our students; we have received few or no complaints about
availability of workstations.
• 152A Architecture Lab. 16 Dell PCs running Windows used for interfacing with breadboards to test circuits. The faculty in charge of the 152A course, teaching assistants
who run the daily lab work, and the computing facility personnel work together to
maintain and upgrade the equipment in this lab.
• 152B Architecture Lab. 12 Dell PCs running Windows used for circuit design and
testing. The faculty in charge of the 152B course, teaching assistants who run the
daily lab work, and the computing facility personnel work together to maintain and
upgrade the equipment in this lab.
• 171L Data Communications Systems Lab. 10 Dell PCs running Windows used for
designing and testing.
Additional Information
We have no additional information.
49
O
Research Highlights
This section describes each regular faculty member’s best research result from 2006–2014.
John Cho. Developed a novel topic model that can automatically classify edges in a graph
based on their topics and popularity (SIGIR’13). For example, when a Twitter user follows
Barack Obama (i.e., a following edge in a Twitter friendship graph), Cho’s model automatically tells us whether it is because the user is interested in politics in general or because
the user simply wants to follow a few well-known people, which happen to include Obama.
This was done through a novel extension to the Latent Dirichlet Analysis (LDA) model. In
experiments on a large-scale real dataset, this model showed significant improvement over
other state-of-the-art methods.
Tyson Condie. MapReduce is a popular framework for data-intensive distributed computing of batch jobs. Condie proposed a modified MapReduce architecture that allows data
to be pipelined between operators. His modified version of the Hadoop MapReduce platform
supports online aggregation and continuous queries, which enables MapReduce programs to
be written for applications such as event monitoring and stream processing.
Jason Cong. Led a team of twelve faculty members from UCLA (the lead institution),
Rice, UC Santa Barbara, and Ohio State, and won a 2009 NSF Expeditions in Computing
Award on Customizable Domain-Specific Computing (CDSC). CDSC looks beyond parallelization and focuses on domain-specific customization as the next disruptive technology
to bring orders-of-magnitude power-performance efficiency improvement. One major point
of progress in CDSC is the development of the accelerator-rich architectures (jointly led
by Jason Cong and Glenn Reinman), including efficient schemes for on-chip accelerator
management (DAC’12), accelerator composition (ISLPED’12, ISLPED’13), memory support
(ISLPED’12) and on-chip network support (ICCAD’13) for accelerator-rich architectures.
Adnan Darwiche. Established the area of knowledge compilation as a main and active
area of research in Artificial Intelligence, with applications to logical and probabilistic reasoning. Darwiche laid the modern foundations of this area, proposed influential compilation
languages, and introduced reductions of probabilistic reasoning to knowledge compilation
that have become standard in the field. His work in this area has also formed the foundation
of some recent influential work in probabilistic databases.
Joseph DiStefano III. Developed two important software projects in medicine and in
systems biology modeling. THYROSIM is an interactive web simulator app for research
and teaching about normal and abnormal human thyroid hormone regulation, based on a
detailed modeling of this physiological system over the past 50 years. COMBOS is a web app
for discovering the limits of information obtainable from nonlinear dynamic systems models,
based on symbolic differential algebra algorithms. Both run flawlessly on handhelds as well
as larger computers.
Michael Dyer. A connectionist controller (Panangadan & Dyer, 2009) enables multiple autonomous agents to construct arbitrary structures in 2D simulated environments by
grasping and dropping fixed-size colored discs. Each agent contains grid-shaped egocentric
spatial maps (ESMs). ESMs specify configurations to be built and guide agents to locations
currently lacking a disc. Agents learn sequences of construction subgoals via reinforcement
learning. Efficient, multiagent cooperation is achieved by path-planning via spreading activation over ESMs.
50
Milos Ercegovac. Proposed a novel efficient design of a radix-16 combined unit for complex division and square root in fixed-point format. Developed a new digit-recurrence algorithm with two-step operand prescaling for complex square root to avoid postscaling of
the result. Implemented designs with different operand precision, and evaluations show that
cost and performance compare favorably with reference designs in terms of area and delay
(IEEE Transactions on Computers, 2012).
Eleazar Eskin. Eskin’s two papers in Genetics (2008) and Nature Genetics (2010) developed mixed models applied to genetic association. The technique (Efficient Mixed Model
Association, or EMMA for short) is now widely used to model relatedness among individuals in genetic studies. The two papers ignited substantial interest in the research topic, and
there are many groups working on extending these techniques.
Eli Gafni. A model M of distributing computing is said to be characterized if we know
how to reduce the question of the solvability of a task T in M, to a topological question. The
characterization of task solvability, known until now only for the wait-free model and the tresilient model, is extended to any model consisting of a subset of runs of the wait-free model
(PODC’14). Depending on Gafni’s conjecture that any meaningful model of distributed
computation is equivalent to some subset of runs, the problem of characterization of task
solvability is complete. Gafni’s characterization improves on the previous characterization of
t-resiliency as it keeps the number of processors and the dimension of the topological space
compatible—a feature missing in the previous characterization.
Mario Gerla. His research since 2006 has focused on mobile networking, for personal and
vehicle applications. Gerla pioneered V2V assisted video downloading to vehicles with “Car
Torrent” (Best Paper WONS06). He innovated it with network coding (robust to intermittence), cognitive radio (robust to interference) and incentives (fair LTE downloading). He
introduced Mobeyes vehicular sensing service, and founded Mobile Vehicular Cloud design
for systematic apps and services support across HW platforms and automakers (SIGCOMM
MVC workshops 2012/13).
Richard E. Korf. One terabyte magnetic disk drive costs less than $100 today, making
disk storage almost a thousand times cheaper than RAM. Korf showed how to replace RAM
with magnetic disks in heuristic search algorithms (J. ACM 2008). The technical challenge
is designing algorithms that replace random access with sequential access. This enables very
large searches, including the first complete breadth-first search of the 15 puzzle, a problem
with over 10 trillion states.
Songwu Lu. The 3G/4G cellular network is a large-scale infrastructure on a par with
the wired Internet. Lu is among the first to analyze its reliability and security. He showed
that the uncovered problems are pervasive in subsystems of mobile data charging, voice
support, mobility management, and control-plane protocols. The root causes lie in both
cellular architecture design tenets and the Internet fundamentals. He is currently designing
a new architecture to address such issues.
Todd Millstein. Contrary to conventional wisdom, Millstein demonstrated how to provide
the most intuitive semantics for multithreading, known as “sequential consistency” (SC),
with minimal performance penalty over the state of the art. The key is to carefully define
the interfaces among all levels of the programming stack in such a way that the hardware and
the compiler retain the flexibility to perform aggressive optimizations while still providing
strong guarantees to programmers.
51
Rafail Ostrovsky. The paper “Fuzzy Extractors: How to Generate Strong Keys from
Biometrics and Other Noisy Data” (SIAM J. Comput. 2008) allowed progress on biometric
identification, was implemented, and has over 1000 citations according to Google Scholar.
The technology allows one to store biometric data (such as fingerprints, retina scans, etc.)
in a secure yet error-correcting way, so that even if the biometric reading is not perfect, the
person can be identified and imposters rejected.
Jens Palsberg. Showed how to do register allocation by puzzle solving (PLDI 2008). The
approach models the register file as a puzzle board and the program variables as puzzle pieces,
and provides an algorithm that solves all the generated puzzles in polynomial time. For
practical use, the puzzle solver was extended with a heuristic for spilling. The implementation
produces competitive x86 code, compared to code produced by a slower, state-of-the-art
algorithm.
Douglass Stott Parker Jr.. Developed the Hypothesis Web, a system for cross-disciplinary
scientific hypothesis development—including collaborative scientific data exploration, literature mining, and hypothesis generation—with, for example, a new scheme for visual analysis
of variance in high-dimensional data. It solves a fundamental problem facing fields like
neuroscience, where hypotheses increasingly range over many scales of science, but domain
experts can master only one.
Miodrag Potkonjak. Developed the concept and several realizations of public PUF. PPUF
is a hardware primitive that enables fast, low-cost and low-energy realization of public key
protocols. More importantly, PPUF enables remote trusted sensing and computation, and
secure and trusted flow of information. Potkonjak also created and implemented several
digital PUFs that can be integrated with regular digital logic and are resilient on all known
side channel attacks.
Glenn Reinman. Explored the use of multi-band radio frequency interconnect (or RFI) to provide shortcuts in a many-core network-on-chip (NoC). Assuming a 400 mm2 die,
Reinman demonstrated that in exchange for 0.13% of area overhead on the active layer, RF-I
can provide an average 13% (max 18%) boost in application performance, corresponding to
an average 22% (max 24%) reduction in packet latency (HPCA 2008).
Amit Sahai. Showed how to construct the first secure general-purpose software obfuscation methods (FOCS 2013, Eurocrypt 2014). This enables a new capability: software that
can keep a secret, even when the software code is entirely captured by an adversary. Sahai is
the founding director of the new NSF Center for Encrypted Functionalities that will further
explore this research area.
Majid Sarrafzadeh. Developed a data-driven analytics engine based on machine learning
algorithms and remote health monitoring data to predict adverse medical events and conditions. Designed and implemented a real-time Exergaming framework to extract data from
wearable body sensors, classify the movements, and derive necessary information. He also
designed a pressure-sensitive bedsheet with important medical applications such as pressure
ulcer risk evaluation, sleep apnea detection, and respiration rate measurement.
Alexander A. Sherstov. Set disjointness is an extensively studied problem in theoretical
computer science, in which k parties must determine with minimal communication whether
k given sets have nonempty intersection, and no party knows all k sets. Prior to Sherstov’s
work, the communication requirements of this problem were only known for small constant k.
Sherstov proved an optimal lower bound on the required communication for every k (STOC
52
2012, STOC 2013, and JACM 2014), closing a long line of research.
Stefano Soatto. Developed a convex optimization framework to detect occlusion regions
in video; occlusions are regions of the scene that are visible from an image but not a temporally adjacent one, and are critical to video compression, object recognition, interaction and
visual interfaces (Intl. J. Comp. Vis. 2012). Introduced the notion of “Detachable Object,”
together with an efficient computational framework to infer them from video (IEEE PAMI
2012). Presented the first analytical characterization of the observability of 3-D motion and
structure from visual and inertial sensors (Intl. J. Rob. Res. 2011).
Yuval Tamir. Pioneered research on software mechanisms for enhancing the resilience
of the software infrastructure of system-level virtualization to hardware and software faults.
Invented, implemented, and evaluated mechanisms for all the components of the virtualization infrastructure – hypervisor, privileged VM, and device driver VMs (NCA 09, VEE 11,
PRDC 11, SERE 12). Achieved recovery rates of 90%+ of detected faults, without the use
of checkpointing, and with negligible overhead during normal operation.
Demetri Terzopoulos. Greatly advanced the state-of-the-art of human simulation, by (1)
developing a uniquely comprehensive biomechanical model of the human body with all the
relevant articular bones, soft tissues, and skeletal muscle controllers capable of synthesizing
realistic actions (ACM TOG 2009), such as autonomous swimming in simulated water (ACM
TOG 2014); and by (2) developing autonomous pedestrian models with nontrivial social
skills, specifically proper door and doorway etiquette.
Wei Wang. To understand the underlying mechanisms of complex traits, it is essential
to study joint genetic effects of multiple single nucleotide polymorphisms (SNPs). Wang
developed an efficient method, FastANOVA (KDD’08), for performing ANOVA tests on
SNP-pairs, with large permutation tests. FastANOVA clusters SNP-pairs by their minor
allele frequencies and derives an upper bound for test values per cluster. These bounds
enable maximal pruning of unnecessary computations while guaranteeing optimal answers.
It delivers two orders of magnitude acceleration over alternative approaches.
Carlo Zaniolo. Discovered and demonstrated: (i) New methods and systems for automatically migrating the database and the applications when the schema changes—also for
supporting historical queries on archived data. (ii) Kleene-closure query extension for data
streams and sequences, along with optimizations based on Visibly Pushdown Automata. (iii)
Solutions to long-enduring problems in logic-based semantics, whereby monotonic aggregates
and greedy algorithms can now be supported—as per the new Datalog system Zaniolo built.
(iv) Methods and systems for analytics of predictable accuracy on massive data sets using sampling and bootstrapping. (v) New text-mining methods and systems for harvesting
structured summaries from document corpora and supporting structured queries on such
summaries. These findings generated many publications in top journals and conferences
(including two best-paper awards) and have impacted the SQL standards and the industry.
Lixia Zhang. Since 2010, the leader of a multicampus team that designs and develops
a new Internet architecture called Named Data Networking (NDN). The team used NDN’s
stateful forwarding plane to develop new solutions that provide multipath forwarding, congestion control, and hijack mitigation all at once (Computer Communications 2013). The
team also designed the “Sync” mechanism, a new architectural building block that uses
NDN’s interest-data exchange communication model to provide efficient and robust data
synchronization for distributed applications (ICNP 2013).
53
P
Honors and Awards
In 2006–2014, the computer science faculty received many major honors and awards, such
as prizes, medals, honorary doctorates, and elections to scientific societies and academies.
They also received eight NSF CAREER Awards, two PECASE Awards, five Sloan Research
Fellowships, ten test-of-time awards, and more than 25 best paper awards, delivered many
keynote addresses, were interviewed for the news, and received teaching awards and other
honors. This section lists awards received by computer science faculty in all categories.
Major Honors and Awards
Leon Alkalai. Elected as member of the International Academy of Astronautics whose
goals include fostering the development of astronautic for peaceful purposes, 2012.
Leon Alkalai. NASA Exceptional Achievement Award and NASA Group Achievement
Award for outstanding technical achievements and contributions to the GRAIL Project,
2012.
Algirdas Avizienis. Eckert-Mauchly Award from the ACM and IEEE Computer Society
for fundamental contributions to fault-tolerant computer architecture and arithmetic, 2012.
Jason Cong. Inventor Recognition Award from the Semiconductor Research Corporation,
2006.
Jason Cong. Elected to ACM Fellow for his contributions to electronic design automation,
2007.
Jason Cong. IEEE Circuits and System (CAS) Society Technical Achievement Award for
seminal contributions to electronic design automation, especially in FPGA synthesis, VLSI
interconnect optimization, and physical design automation, 2010.
Jason Cong. ACM/IEEE A. Richard Newton Technical Impact Award in Electronic
Design Automation for pioneering work on technology mapping for FPGAs, 2011.
Jason Cong. 50th Design Automation Conference Prolific Author Award for publishing
40-49 papers in the first 50 years of DAC, 2013.
Adnan Darwiche. First-place gold medal winner (with graduate student Knot Pipatsrisawat) in the 2007 International SAT competition for their satisfiability solver, Rsat, 2007.
Adnan Darwiche. Election to Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) for significant contributions to the development and application of
probabilistic and logical methods in automated reasoning, 2007.
Milos Ercegovac. Distinguished Alumni Educator Award from the University of Illinois
at Urbana-Champaign for outstanding contributions to computer science education, 2013.
Deborah Estrin. First ACM-W Athena Lecturer Award. Selected from a list of 14 top
women in the field of computer science, 2006.
Deborah Estrin. Women of Vision Award from the Anita Borg Institute in recognition of
significant contributions to technology innovation, 2007.
Deborah Estrin. Election to Fellow of the American Academy of Arts and Sciences for
preeminent contributions to her discipline and to society at large, 2007.
Deborah Estrin. Doctorate Honoris Causa from the Swiss Federal Institute of Technology
in Lausanne, 2008.
54
Deborah Estrin. Elected to the National Academy of Engineering for her pioneering design and application of heterogeneous wireless sensing systems for environmental monitoring,
2009.
Gerald Estrin. Israeli Software Industry Pioneer Award in recognition of the leadership
and outstanding achievements put forth in creating the first computer in Israel, 2006.
Eli Gafni. Honored (with Hebrew University’s Danny Dolev) at the Symposium on
Principles of Distributed Computing (PODC). Their work is highlighted in a two-hour, eightspeaker program entitled “Landmarks in Distributed Computing: Celebrating the Research
of Dolev and Gafni,” 2010.
Mario Gerla. Northrop Grumman Corp. $5000 prize for the best publication record
relevant to NGC, 2009.
Mario Gerla. MILCOM Technical Achievement Award in recognition of outstanding
contributions to military communications, 2011.
Mario Gerla. IEEE Communications Society Technical Recognition Award for contributions in ad hoc and sensor networks, 2011.
David Heckerman. Elected to ACM Fellow based on significant contributions to reasoning
and decision-making under uncertainty, 2011.
Alan Kay. Honorary Doctorate from Georgia Tech. First computationalist to receive an
honorary degree from Georgia Tech, 2006.
Alan Kay. Honoris Causa Degree in Informatica from the University of Pisa, Italy for
contributions to the development of the personal computer and object-oriented programming,
2007.
Alan Kay. Elected ACM Fellow for his fundamental contributions to personal computing
and object-oriented programming, 2008.
Alan Kay. Honorary Doctorate, Mathematics, University of Waterloo, Ontario, Canada,
2008.
Alan Kay. Honorary Doctorate, Informatics/Computer Science, Kyoto University, Japan,
2009.
Alan Kay. Honorary doctorate (Doctor Honoris Causa) from the University of Murcia,
Spain, for his contributions to the development of the personal computer and object-oriented
programming, 2010.
Alan Kay. Honorary Doctorate, Computer Science, DePaul University, Chicago, 2012.
Leonard Kleinrock. Computer and Communications Prize for contributions to establishing the foundation of today’s Internet technology through the concept of packing switching
(with Robert Kahn and Lawrence Roberts), 2006.
Leonard Kleinrock. Awarded the National Medal of Science for “fundamental contributions to the mathematical theory of modern data networks, for the functional specification of
packet switching which is the foundation of the Internet Technology, for mentoring generations of students, and for leading the commercialization of technologies that have transformed
the world.” Kleinrock was presented with the medal at a White House ceremony, 2008.
Leonard Kleinrock. Doctor Scientiarum Honoris Causa (Honorary Doctorate of Science)
from the Technion-Israel Institute of Technology in recognition of his seminal work on Internet communication and his contributions to the mathematical theory of modern data
networks, 2010.
55
Leonard Kleinrock. Dan David Prize (Tel Aviv Univ., Israel) for his research contributions
in communications networks, establishing the fundamental principles upon which many of
the most important aspects of information communication and the Internet are based, 2010.
Leonard Kleinrock. Inaugural induction to the Internet Hall of Fame for those who were
instrumental in the early design and development of the Internet, 2012.
Leonard Kleinrock. Elected Eminent Member of IEEE’s Electrical and Computer Engineering Honor Society (Eta Kappa Nu) for technical contributions to society through leadership in the fields of electrical and computer engineering that resulted in significant benefits
to humankind, 2012.
Leonard Kleinrock. Alexander Graham Bell Medal for pioneering contributions to modeling, analysis and design of packet-switching networks, 2012.
Leonard Kleinrock. Honorary Doctorate from Concordia University, Montreal, Canada,
2013.
Eddie Kohler. New Faculty Fellowship Award from Microsoft Research which recognizes
and supports exceptional new faculty members who are engaged in innovative computing
research, 2006.
Eddie Kohler. Young Innovator Award for creating Asbestos, an operating system that
ensures the security of personal data. Awarded by MIT’s Technology Review which honors
young innovators under age 35, 2006.
Richard Muntz. ACM SIGMETRICS Achievement Award recognizing individuals who
have made highly influential contributions to the theory or practice of computer and communication system performance evaluation, 2006.
Carey Nachenberg. Technology Innovation Award (computer security category) from the
Wall Street Journal for a new technology invented by Nachenberg, called Quorum, 2010.
Ani Nahapetian. Outstanding Engineering Achievement Merit Award from the Engineers
Council, 2012.
Stanley Osher. Elected to the American Academy of Arts and Sciences, 2009.
Stanley Osher. Honorary Doctoral degree, Hong Kong Baptist University, 2009.
Stanley Osher. Elected Fellow of Society of Industrial and Applied Mathematics (SIAM),
2009.
Stanley Osher. Named American Mathematical Society Fellow, 2011.
Rafail Ostrovsky. Pazy Memorial Research Award from the USA-Israel Binational Science
Foundation, 2012.
Rafail Ostrovsky. Elected IACR Fellow by the International Association for Cryptologic
Research in recognition of his technical and professional contributions to that field, 2013.
Jens Palsberg. ACM SIGPLAN Service Award in recognition of the value and degree of
service to the programming languages community, 2012.
Judea Pearl. Purpose Prize, an inaugural award from Civic Ventures that recognizes
individuals or teams who work to solve society’s problems. Awarded for promoting MuslimJewish understanding, 2006.
Judea Pearl. Honorary Doctor of Science from the University of Toronto in recognition
of groundbreaking contributions to the field of computer science and efforts to promote
cross-cultural dialogue and reconciliation, 2007.
Judea Pearl. Honorary Doctor of Humane Letters degree from Chapman University,
2008.
56
Judea Pearl. Benjamin Franklin Medal in Computer & Cognitive Science for creating the
first general algorithms for computing and reasoning with uncertain evidence, 2008.
Judea Pearl. Rumelhart Prize from the Cognitive Science Society for his leading research
in artificial intelligence and systems that reason plausibly from uncertain evidence, 2010.
Judea Pearl. Induction into the Artificial Intelligence Hall of Fame by IEEE Intelligent
Systems for his seminal contributions to the field of artificial intelligence, 2011.
Judea Pearl. ACM Turing Award for innovations that have enabled remarkable advances
in the partnership between humans and intelligence, 2011.
Judea Pearl. Harvey Prize in Science and Technology (with Sir Richard Friend of Cambridge University) for laying the theoretical foundations for knowledge representation and
reasoning in computer science, 2011.
Judea Pearl. Election to the American Academy of Arts and Sciences in recognition of
his outstanding accomplishments, 2012.
Judea Pearl. Lyford Lecture and Distinguished Alumni Award, New York University
Polytechnic, November 2013.
Judea Pearl. Elected to the National Academy of Sciences in recognition of distinguished
and continuing achievements in original research, 2014.
Judea Pearl. Honorary Doctorate Degree, Texas A&M University, May 2014.
Amit Sahai. Pazy Memorial Research Award from the USA-Israel Binational Science
Foundation, 2012.
Stefano Soatto. Elected IEEE Fellow for contributions to dynamic visual processes, 2013.
Demetri Terzopoulos. Scientific & Technical Achievement Award from the Academy of
Motion Picture Arts & Sciences for pioneering work in physically based computer-generated
techniques used to simulate realistic cloth in motion pictures, 2006.
Demetri Terzopoulos. Elected a Fellow of the Royal Society of Canada (highest academic
accolade available to scientists and scholars in Canada), 2006.
Demetri Terzopoulos. Elected to ACM Fellow for contributions to computer graphics and
vision, 2007.
Demetri Terzopoulos. Inaugural recipient of the IEEE PAMI-TC Computer Vision Significant Researcher Award for his pioneering and sustained research on deformable models
and their applications, 2007.
Demetri Terzopoulos. Guggenheim Fellowship—awarded to individuals who have shown
stellar achievement and exceptional promise for continued accomplishment, 2009.
Demetri Terzopoulos. Inaugurated as an EETN Honorary Member of the Hellenic Artificial Intelligence Society in recognition for his pioneering work in the field of artificial
intelligence, 2010.
Demetri Terzopoulos. Keck Futures Initiative Award from the National Academies for
research on “A Multilinear (Tensor) Algebraic Framework for Multifactor Manifold Learning
With Applications to Image Science,” 2011.
Demetri Terzopoulos. Elected to Fellow of the Royal Society (in London) for his work in
computer vision and computer graphics, 2014.
Wei Wang. IEEE ICDM Outstanding Service Award for major contributions to the
promotion of data mining as a field and to ICDM as the premier research conference on data
mining, 2012.
57
Alan Yuille. Named an IEEE Fellow for contributions to computer and biological vision,
medical image processing and computational theories of cognition, 2008.
Lixia Zhang. Elected to ACM Fellow for contributions to protocol designs for packet
switched networks, 2006.
Lixia Zhang. IEEE Internet Award for contributions toward an understanding of the
complex interactions between Internet components and the development of the Internet
architecture, 2009.
Song-Chun Zhu. J. K. Aggarwal Prize for fundamental and pioneering contributions to
a unified foundation for visual pattern conceptualization, modeling, learning, and inference
with applications in computer vision and pattern recognition, 2008.
Song-Chun Zhu. Elected to IEEE Fellow for contributions to statistical modeling, learning and inference in computer vision, 2010.
NSF CAREER, PECASE, and Sloan Research Fellowships
Tyson Condie. NSF CAREER Award for his research on “Towards a Big Data Application Server Stack,” 2014.
Eleazar Eskin. Sloan Research Fellowship for his work in the field of molecular biology,
2009.
Jason Ernst. NSF CAREER Award for expanding the dimensions of computational
epigenomic modeling and analysis, 2013.
Jason Ernst. Sloan Research Fellowship in recognition of distinguished performance and
a unique potential to make substantial contributions to a scientific field, 2013.
Eddie Kohler. NSF CAREER Award supporting early-career activities of faculty who
effectively integrate research and education, 2006.
Eddie Kohler. Presidential Early Career Award for Scientists and Engineers (PECASE)
from NSF, which is the highest honor bestowed by the government on science and engineering
professionals in the early stages of their careers, 2007.
Eddie Kohler. Sloan Research Fellowship in recognition of faculty who show the most
outstanding promise toward making fundamental contributions to new knowledge, 2007.
Rupak Majumdar. NSF CAREER Award supporting early-career activities of faculty
who effectively integrate research and education, 2006.
Rupak Majumdar. Sloan Research Fellowship for work on formal verification techniques,
2010.
Todd Millstein. NSF CAREER Award supporting early-career activities of faculty who
effectively integrate research and education, 2006.
Alexander Sherstov. NSF CAREER Award based on the scientific and technical merits
of his proposed project “Limits of Communication,” 2012.
Alexander Sherstov. Alfred P. Sloan Research Fellowship—awarded to early-career scholars who represent the most promising scientific researchers working today, 2014.
Zhuowen Tu. NSF CAREER Award for research on holistic 3D brain image parsing,
2009.
Jennifer Wortman Vaughan. NSF CAREER Award for her research on Learning and
Incentives-Based Techniques for Aggregating Community-Generated Data, 2010.
58
Jennifer Wortman Vaughan. Presidential Early Career Award for Scientists and Engineers (PECASE) from NSF, which is the highest honor bestowed by the government on
science and engineering professionals in the early stages of their careers, 2012.
Test of Time Awards
The following test-of-time awards were given to papers with multiple authors; we list only
the faculty members.
Algirdas Avizienis. Jean-Claude Laprie Award in Dependable Computing for 1967 paper
“Design of Fault-Tolerant Computers.” (Papers at least 10 years old that have significantly
influenced the theory and/or practice of dependable computing.) Awarded in 2012.
John Cho. Ten-Year Best Paper Award from the International Conference on Very Large
Data Bases (VLDB 2000) for his paper “Evolution of the Web and Implications for an
Incremental Crawler” (coauthored with Hector Garcia-Molina). Awarded in 2010.
Jason Cong. Most Significant Contributions to FPGA International Symposium. ACM
SIGDA recognizes Cong for two collaborative papers published in the 1992 to 2001 time
frame. Awarded in 2012.
Petros Faloutsos. Test-of-Time Award from ACM SIGCOMM. “On Power-Law Relationships of the Internet Topology” published in 1999 is authored by brothers Michalis Faloutsos
(UCR), Petros Faloutsos (UCLA), and Christos Faloutsos (CMU). Citeseer reports the paper
as the 4th most sited of all papers published in 1999. Awarded in 2010.
Leonard Kleinrock. ACM SIGCOMM Test-of-Time Award recognizes notable papers
published between 1969 and 1995. Included are Kleinrock’s “Research Areas in Computer
Communication,” July 1974 and “Nomadic Computing—An Opportunity,” January 1995.
Awarded in 2006.
Rupak Majumdar. Most Influential POPL Paper Award for the 2003 paper “Abstractions
from proofs.” Awarded in 2014.
Todd Millstein and Rupak Majumdar. ACM SIGPLAN Award for Most Influential PLDI
Paper for their 2001 paper “Automatic Predicate Abstraction of C Programs.” Awarded in
2011.
Richard Muntz. 2006 paper, “Catch the moment; maintaining closed frequent itemsets
over a data stream sliding window” (published in Knowledge and Information Systems), is
selected by ICDM to receive Highest Impact Paper Award for 2013.
Demetri Terzopoulos. The Helmholtz Test-of-Time Award from the IEEE Computer Society for the paper “Snakes: Active Contour Models,” presented at the first ICCV conference
in 1987. Awarded in 2013.
Song-Chun Zhu and Alan Yuille. The Helmholtz Test-of-Time Award from the IEEE
Computer Society for the paper “Region Competition: Unifying Snakes, Region Growing, Energy/Bayes/MDL for Multi-band Image Segmentation,” presented at ICCV 1995.
Awarded in 2013.
Best Paper Awards
Many of the following best paper awards were given to papers with multiple authors; we list
only the faculty members.
59
Jason Cong and Glenn Reinman. Best paper award for “CMP Network-on-Chip Overlaid
with Multi-Band RF-Interconnect” at 14th International Symposium on High Performance
Computer Architecture, 2008.
Jason Cong. Best paper award for “FCUDA: Enabling Efficient Compilation of CUDA
Kernels onto FPGAs” at 7th IEEE Symposium on Application Specific Processors, 2009.
Jason Cong. Best paper award for “Multilevel Granularity Parallelism Synthesis on
FPGAs” at IEEE International Symposium on Field-Programmable Custom Computing
Machines, 2011.
Jason Cong. ACM best paper award for “Behavior-Level Observability Analysis for Operation Gating in Low-Power Behavioral Synthesis,” at the Design Automation Conference,
2012.
Jason Cong. Best paper award for “Improving Polyhedral Code Generation for HighLevel Synthesis,” at International Conference on HardwareSoftware Codesign and System
Synthesis, 2013.
Jason Cong. Best paper award for “Polyhedral-Based Data Reuse Optimization for
Configurable Computing,” at 21st ACM/SIGDA International Symposium on Field Programmable Gate Arrays, 2013.
Jason Cong. ACM TODAES best paper award for “Automatic Memory Partitioning and
Scheduling for Throughput and Power Optimization,” 2013.
Adnan Darwiche. Best student paper award for “On the Power of Clause-Learning SAT
Solvers with Restarts,” at 15th International Conference on Principles and Practice of Constraint Programming, 2009.
Mario Gerla. Best paper award for “CapStart: An Adaptive TCP Slow Start for High
Speed Networks” at Internet 2009.
Boris Kogan. Best paper award for “Defibrillation Failure and Tachycardia-Induced Early
Afterdepolarizations: A Simulation Study,” at the International Conference on Computational Biology, 2008.
Todd Millstein. Best paper award for “Deriving State Machines from TinoOS Programs
Using Symbolic Execution” at International Conference on Information Processing in Sensor
Networks, 2008.
Todd Millstein. 2012 paper, “End-to-End Sequential Consistency,” is selected in 2013 by
Top Picks (IEEE Micro Magazine) as one of the most significant research papers in computer
architecture for that year.
Stanley Osher. Thomson Reuters Essential Science Indicators featured the paper “The
Split Bregman Method for L1-Regularized Problems” as a “New Hot Paper in the Field of
Computer Science” in 2011 because the paper was one of the most-cited papers in computer
science in 2009–2011.
Rafail Ostrovsky. Best paper award for “Visual Cryptography on Graphs” at COCOON,
2008.
Miodrag Potkonjak. Best paper award for “Optimizing the Configuration and Control
of a Novel Human-Powered Energy Harvesting System,” at the International Workshop on
Power and Timing Modeling, Optimization and Simulation, 2013.
Amit Sahai. “Predicate Encryption Supporting Disjunctions, Polynomial Equations, and
Inner Products” selected as one of the top four papers at Eurocrypt, 2008.
60
Amit Sahai. “Resolving the Simultaneous Resettability Conjecture and a New NonBlack-Box Simulation Strategy” selected for special journal issue of SICOMP that features
the best papers from the 2009 IEEE Symposium on Foundations of Computer Science, 2009.
Majid Sarrafzadeh. Best paper award for “Ubiquitous Personal Assistive System for
Neuropathy,” at HealthNet, 2008.
Majid Sarrafzadeh. Best paper award for “The SmartCane System: An assistive Device
for Geriatrics,” at BodyNets, 2008.
Majid Sarrafzadeh and Ani Nahapetian. Best paper award for “Bayesian Networks-Based
Interval Training Guidance System for Cancer Rehabilitation” at the International Conference on Mobile Computing Applications, 2009.
Demetri Terzopoulos. CDSC Outstanding Paper for “Virtual Vision and Smart Cameras,” selected as one of the best papers of the First ACM/IEEE International Conference
on Distributed Smart Cameras, Vienna, Austria, September 2007.
Demetri Terzopoulos. Graphical Models Top Cited Article 2005–2010 award for “Autonomous Pedestrians,” which was published in 2007. Awarded in 2010.
Wei Wang. SIGKDD best research paper award for “FastANOVA: an efficient algorithm
for genome-wide association study,” 2008.
Wei Wang. ICDE best student paper award for “CARE: finding local linear correlations
in high dimensional data,” 2008.
Carlo Zaniolo. SIGMOD best paper award for “High-Performance Complex Processing
over XML Streams,” 2012.
Carlo Zaniolo. Best paper award for “Fast Computation of Approximate Based Histograms on Sliding Windows Over Data Streams,” at 25th International Conference on
Scientific and Statistical Database Management, 2013.
Lixia Zhang. Best paper award for “Investigating occurrence of duplicate updates in
BGP announcements,” Passive and Active Measurements Conference, 2010.
Song-Chun Zhu. Marr Prize honorary mention for “Deformable Template as Active
Basis,” presented at ICCV, 2007.
Keynote and Distinguished Lectures
Jason Cong. Keynote speaker, ASAP 22nd IEEE International Conference on ApplicationSpecific Systems, Architectures and Processors, 2011.
Jason Cong. Keynote speaker, 31st IEEE International Conference on Computer Design,
October 2013.
Jason Cong. Keynote speaker, “Computing Beyond Processors,” at IEEE International
Symposium on Circuits and Systems, May 2013.
Mario Gerla. Keynote speaker, IEEE’s 7th International Wireless Communications and
Mobile Computing Conference, Turkey, 2011.
Mario Gerla. Keynote speaker, 9th IEEE International Conference on Ad Hoc and Sensor
Systems, Nevada, 2012.
Mario Gerla. Keynote speaker, NIST Forum: The Intersection of Cloud and Mobility,
Washington DC, 2014.
Mario Gerla. Keynote speaker, SBRC 2014, Forianopolis, Brasil, May 2014.
Mario Gerla. Keynote speaker, ISCC 2014 Conference in Madeira, Portugal, June 2014.
61
Leonard Kleinrock. Keynote speaker, WCNC, Hong Kong, 13 March.
Leonard Kleinrock. E. Leonard Arnoff Memorial Lecture on “A Brief History of the
Internet and its Dynamic Future,” U. of Cincinnati’s College of Business, 2011.
Stanley Osher. Plenary speaker, International Conference of Mathematicians, 2010.
Stanley Osher. John von Neumann lecturer, SIAM annual meeting, 2013.
Rafail Ostrovsky. Keynote speaker, 10th International Conference on Theory and Practice of Public Key Cryptography, hosted by the Institute for Theoretical Science, Tsinghua
University, Beijing, 2007.
Rafail Ostrovsky. Plenary talk, “Position-Based Quantum Cryptography: Impossibility
and Constructions,” Quantum Information Processing Workshop, 2011.
Jens Palsberg. Lecturer in the Evans and Sutherland Distinguished Lecture Series at the
University of Utah, Salt Lake City, Utah, March 2006.
Jens Palsberg. Keynote speaker, Computing: The Australasian Theory Symposium,
Ballarat, Australia, 2007.
Jens Palsberg. ACM Distinguished Lecturer, University of Canterbury, Christchurch,
New Zealand, February 2008.
Jens Palsberg. ACM Distinguished Lecturer, University of Waikato, Hamilton, New
Zealand, February 2008.
Jens Palsberg. ACM Distinguished Lecturer, University of Alberta, Edmonton, Canada,
September 2008.
Jens Palsberg. ACM Distinguished Lecturer, University of Victoria, British Columbia,
Canada, September 2008.
Jens Palsberg. Keynote speaker, IEEE International Conference on Embedded Software
and Systems, Hangzhou, China, 2009.
Jens Palsberg. Distinguished Lecture at Aarhus University, Denmark, September 2010.
Jens Palsberg. ACM Distinguished Lecturer, University of Arkansas, April 2011.
Jens Palsberg. Distinguished Lecture at University of Chicago, May 2011.
Jens Palsberg. Distinguished Lecture at University of Technology, Sydney, August 2011.
Jens Palsberg. Keynote speaker, Formal Techniques for Java-like Programs, Beijing,
China, 2012.
Jens Palsberg. Keynote speaker, Static Analysis Symposium, Deauville, France, 2012.
Jens Palsberg. ACM Distinguished Lecture, Auburn University, Nov 2013.
Judea Pearl. Medallion Lecture 2013, Institute of Mathematical Statistics, an international scholarly society devoted to the development and dissemination of the theory and
applications of statistics and probability.
Amit Sahai. Keynote speaker, 12th Annual International Conference on Information
Security, 2009.
Majid Sarrafzadeh. Keynote speaker, Eighth Annual Healthcare Unbound Conference,
2011.
Alexander Sherstov. Plenary speaker, 39th International Symposium on Mathematical
Foundations of Computer Science, Budapest, August 2014.
Stefano Soatto. Keynote speaker, Workshop on Dynamic Vision, Kyoto, Japan, 2009.
Stefano Soatto. Distinguished lecturer, UC Irvine, May 2009.
Stefano Soatto. Plenary speaker, Intl Conference on the Dynamics of Information Systems, Gainesville FL, January 2009.
62
Stefano Soatto. Distinguished Lecturer, ONR China Lake, 2010.
Stefano Soatto. Aziel Rosenfeld Distinguished Lecture, University of Maryland, 2010.
Stefano Soatto. Keynote speaker, Intl Workshop on Information Theory in Computer
Vision and Pattern Recognition, Barcelona, 2011.
Stefano Soatto. Keynote speaker, Robotic Vision Workshop, ICCV, 2011.
Stefano Soatto. Keynote speaker, Workshop on Mobile Manipulation, ICRA, 2011.
Stefano Soatto. Plenary speaker, Mathematics and Image Analysis, Henry Poincare Institute, Paris FR, January 2012.
Stefano Soatto. Keynote speaker, IEEE GlobalSIP, Atlanta GA, December 2014.
Stefano Soatto. Distinguished seminar speaker (Science, Technology and Innovation Seminar), University of Minnesota, April 2014.
Stefano Soatto. Plenary speaker, CVPR Workshop on Long-Term Detection and Tracking, 2014.
Demetri Terzopoulos. Plenary speaker, ACM SIGGRAPH 10th Anniversary Conference,
Tokyo, Japan, June 2006.
Demetri Terzopoulos. Distinguished lecturer, Colloquium Jacques Morgenstern, INRIA,
Sophia-Antipolis, France, December 2006.
Demetri Terzopoulos. Distinguished lecturer, Sterling Hou Distinguished Lecture Series,
College of Engineering, University of Missouri, November 2006
Demetri Terzopoulos. Distinguished lecturer, Computer Science Department, University
of Genova, Italy, September 2006.
Demetri Terzopoulos. Distinguished lecturer, Computer Science and Engineering Distinguished Lecture Series, University of California Riverside CA, October 2007.
Demetri Terzopoulos. Distinguished lecturer, Computer Vision Distinguished Speaker
Series, Computer Science Department, University of Central Florida, Orlando FL, October,
2007.
Demetri Terzopoulos. Distinguished lecturer, Center of Excellence for Pattern Recognition Distinguished Speaker Series, Univ. of So. Florida, Tampa, October 2007.
Demetri Terzopoulos. Distinguished lecturer, Barr Systems Distinguished Lecture Series
in Computer Science, University of Florida, Gainesville, October 2007.
Demetri Terzopoulos. Keynote speaker, UCLA Computer Science Alumni Reception,
Google, Inc., Irvine CA, September 2007.
Demetri Terzopoulos. Keynote speaker, Sixth International Conference on 3D Digital
Imaging and Modeling (3DIM’07), Montreal, PQ, August, 2007.
Demetri Terzopoulos. Keynote speaker, Cognitive Animation Workshop, Yosemite CA,
June 2008.
Demetri Terzopoulos. Plenary speaker, International Joint Conference on Autonomous
Agents and Multiagent Systems, Estoril, Portugal, May 2008.
Demetri Terzopoulos. Keynote speaker, 2nd IEEE International Workshop on Human
Motion: Understanding, Modeling, Capture and Animation, Rio de Janeiro, Brazil, October
2008.
Demetri Terzopoulos. Keynote speaker, 10th International Conference on ComputerAided Design and Computer Graphics, Beijing, China, October 2008.
Demetri Terzopoulos. Keynote speaker, 5th International Symposium on Visual Computing, Las Vegas NV, November 2009.
63
Demetri Terzopoulos. Distinguished lecturer, Distinguished Speaker Seminar Series, Center for Imaging Science, Johns Hopkins University, Baltimore MD, November 2009.
Demetri Terzopoulos. Keynote speaker, 14th Portuguese Conference on Artificial Intelligence (EPIA 2009), Aveiro, Portugal, October 2009.
Demetri Terzopoulos. Keynote speaker, 2nd ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing (VIPIMAGE 2009), Porto, Portugal, October 2009.
Demetri Terzopoulos. Plenary speaker, 6th IEEE International Conference on Advanced
Video and Signal Based Surveillance (AVSS 09), Genova, Italy, September 2009.
Demetri Terzopoulos. Keynote speaker, ACM Genetic and Evolutionary Computation
Conference (GECCO 2009), Montreal, PQ, July 2009.
Demetri Terzopoulos. Plenary speaker, Midwest Conference on Mathematical Methods
for Images and Surfaces, Michigan State University, April 2009.
Demetri Terzopoulos. Keynote speaker, 11th SPIE Conference on Electroactive Polymer
Actuators and Devices (EAPAD), San Diego CA, March 2009.
Demetri Terzopoulos. Distinguished lecturer, College of Engineering Distinguished Speaker
Series, University of Texas, Arlington, December 2010.
Demetri Terzopoulos. Distinguished lecturer, Computer Science Department Distinguished Lecturer Series, University of California Irvine CA, June 2010.
Demetri Terzopoulos. Keynote speaker, 3rd International Conference on Pervasive Technologies Related to Assistive Environments, Samos, Greece, June 2010.
Demetri Terzopoulos. Keynote speaker, 6th Hellenic Conference on Artificial Intelligence
(SETN 2010), Athens, Greece, May 2010.
Demetri Terzopoulos. Keynote speaker, ACM SIGGRAPH Symposium on Interactive
3D Graphics and Games (I3D 2010), Bethesda MD, February 2010.
Demetri Terzopoulos. Keynote speaker, First IEEE Workshop on Modeling, Simulation,
and Visual Analysis of Large Crowds, Barcelona, Spain, November 2011.
Demetri Terzopoulos. Keynote speaker, IEEE International Conference on Multimedia
Technology (ICMT 2011), Hangzhou, China, July 2011.
Demetri Terzopoulos. Plenary speaker, IEEE International Conference on Multimedia
and Expo (ICME 2011), Barcelona, Spain, July 2011.
Demetri Terzopoulos. Keynote speaker, First IEEE Workshop on Camera Networks and
Wide-Area Scene Analysis, Colorado Springs CO, June 2011.
Demetri Terzopoulos. Distinguished lecturer, Distinguished Speaker Series, Computer
and Information Science Department Indiana Univ.-Purdue Univ. IN, April 2011.
Demetri Terzopoulos. Keynote speaker, Eighth IEEE Intl Conference on Intelligent Information Hiding and Multimedia Signal Processing, Athens, Greece, July 2011.
Demetri Terzopoulos. Keynote speaker, First IEEE Workshop on Vision Meets Cognition:
Functionality, Physics, Intentionality, & Causality, Columbus OH, June 2014.
Demetri Terzopoulos. Distinguished lecturer, Distinguished Speaker Series, Department
of Computer Science, Wayne State University, Detroit MI, January 2014.
Demetri Terzopoulos. Keynote speaker, NOAA Fisheries Stock Assessment Workshop,
National Academy of Sciences, Washington, DC, May 2014.
Wei Wang. Keynote speaker, 12th Francophone International Conference on Mining and
Knowledge Management, Bordeaux FR, 2012.
64
Wei Wang. Keynote speaker, Artificial Intelligence Forum, Taiwan, 2014.
Wei Wang. Keynote speaker, International Conference on Data Science, Beijing, China,
2014.
Lixia Zhang. Keynote speaker, Latin America Networking Conference, 2011.
Lixia Zhang. Keynote speaker, Asian Internet Engineering Conference, 2011.
Lixia Zhang. Keynote speaker, IEEE/ACM IWQoS Symposium, 2013.
Google, IBM, and Okawa Awards
John Cho. Okawa Foundation Research Award, 2006.
Jason Cong. IBM Faculty Award presented to individuals for the quality of their work
and its importance to industry, 2006.
Jason Cong. IBM Faculty Award in recognition of his achievements and the quality of
his research programs, 2007.
Jason Cong. IBM Faculty Award in recognition of his research and its importance to
industry, 2012.
Milos Ercegovac. Okawa Foundation Research Award based on research efforts in the
fields of information and telecommunications, 2006.
Eleazar Eskin. Okawa Foundation Research Award based on the merits of an individual’s
research efforts in the fields of information and telecommunications, 2008.
Deborah Estrin. Google Focused Research Award which gives Estrin access to Google’s
tools, technologies and expertise, 2010.
Todd Millstein. IBM Faculty Award designed to foster collaboration and promote curriculum innovation, 2008.
Rafail Ostrovsky. IBM Faculty Award presented to individuals for the quality of their
work and its importance to industry, 2006.
Jens Palsberg. IBM Faculty Award presented to individuals for the quality of their work
and its importance to industry, 2006.
Amit Sahai. Okawa Foundation Research Award for “Cryptographic Techniques for Encrypted Data,” 2008.
Amit Sahai. Rethinking Encryption Award from Google for leading the development of
new notions of encryption to provide security and usability suitable for cloud computing and
general networked environments, 2010.
Demetri Terzopoulos. Okawa Foundation Research Award for “Realistic Human Simulation,” 2011.
Wei Wang. Okawa Foundation Research Award, 2013.
Teaching Awards
John Cho. Northrop Grumman Excellence in Teaching Award, 2006.
Paul Eggert. Lockheed Martin Excellence in Teaching Award—presented to faculty members who continue to dedicate an abundance of talent, time and energy to teaching, 2012.
Milos Ercegovac. Lockheed Martin Excellence in Teaching Award based on the quality of
classroom teaching, contributions to curriculum development, high personal and professional
standards, and high scores on student teaching evaluations, 2009.
65
David Smallberg. Lockheed Martin Excellence in Teaching Award based on the quality of
classroom teaching, contributions to curriculum development, high personal and professional
standards, and high scores on student teaching evaluations, 2008.
Interviews, Research Highlights, Magazines, TV, Radio
Jason Cong. U.S. News and World Report features a July 2010 article featuring the
Center for Domain-Specific Computing, led by Jason Cong.
Eleazar Eskin. The paper “A Sequence-Based Variation Map of 8.27 Million SNPs i8n Inbred Mouse Strains” is featured in the August 2007 issue of Nature; it focuses on determining
the genes related to the susceptibility to environmental disease.
Eleazar Eskin. The New York Post publishes an article in their 21 October 2012 edition that describes the human genetics research being carried out by Eskin with his UCLA
research team and Tel Aviv University. The Post refers to it as “genetic GPS.”
Deborah Estrin. Ranked No. 2 worldwide in the field of computer science according to
h-index in the August 2007 issue of Nature.
Leonard Kleinrock. The October 2007 issue of PC World ranks, in order of importance,
its selections for “The 16 Greatest Moments in Web History.” UCLA, Leonard Kleinrock,
ARPAnet, and the famous first message are featured as the No. 4 greatest moment. (Google
is ranked as No. 3, Netscape as No. 2, and the creation of the Web is ranked as No. 1.)
Leonard Kleinrock. “An Oral History of the Internet. How the Web Was Won” is featured
in the July 2008 issue of Vanity Fair. The article contains photos and insightful comments
from Professor Leonard Kleinrock and alumnus Vint Cerf.
Leonard Kleinrock. Featured in the March 2009 issue of Los Angeles Magazine. Called
“Feature Shock,” the article is a result of a lengthy interview with Kleinrock, who discusses
the history behind today’s Internet, his own personal history, and what he envisions for our
future in cyberspace.
Leonard Kleinrock. Featured in a Q&A interview in the August 2013 edition of IEEE’s
Computer Magazine.
Giovanni Pau. BBC Digital Planet interview in June 2008 regarding his work on a
car-based mesh networking system that allows web connectivity, video conferencing and the
opportunity to map each vehicle’s whereabouts in real time on an interactive map.
Judea Pearl. Featured on the cover of the June 2012 issue of Communications of the
ACM, followed by an article (“Game Changer”) that explores his background and work on
artificial intelligence, probability, and casual reasoning.
Judea Pearl. Honored in an August 2013 special issue of the Cognitive Science Journal.
Judea Pearl. Featured in an October 2013 Q&A interview in Statistics Views.
Amit Sahai. Research on zero-knowledge is featured in the 26 April 2007 issue of Nature.
Entitled “The Security of Knowing Nothing,” the article describes Sahai’s research which
focuses on developing new zero-knowledge proofs and related cryptographic techniques for
use on the Internet.
Amit Sahai. Appearing on the LA Fox 10 o’clock evening news (14 November 2007) in
a segment on cybersecurity–in particular, the vulnerability of the Internet infrastructure to
hacker attacks.
66
Amit Sahai. BBC Digital Planet interview in May 2008 regarding his work on “functional
encryption” (joint research with UCLA alumnus Brent Waters) that one day could have an
impact on how data is encrypted, stored and decrypted.
Amit Sahai. Featured in the 2014 issue of Quanta Magazine. The article, “Perfecting the
Art of Sensible Nonsense,” describes Sahai’s dedication to creating a technology for solving
many of the problems that have driven cryptography for the past four decades.
Demetri Terzopoulos. Quoted in 2006 Millimeter Magazine in “Oscar’s New Clothes.”
Demetri Terzopoulos. Quoted in the 2006 Seattle Times March 2nd story, “Microsoft
Researcher Honored as Computer-Graphics Pioneer.”
Demetri Terzopoulos. Quoted in 2006 February 20th Wired News, in story “Gizmos
Trump Gowns at Nerd Oscars.”
Demetri Terzopoulos. Featured in 2006 Discovery Channel production “Science on the
Red Carpet,” a one-hour special hosted by Dave Foley, which “goes to the 2006 Scientific and
Technical Academy Awards as the Academy of Motion Picture Arts and Sciences gathers to
honor the behind-the-scenes creative geniuses that make movies so memorable.”
Demetri Terzopoulos. “Virtual Extras” is featured in December 2007 on-line issue of
MIT’s Technology Review. The article describes how Terzopoulos’ “autonomous pedestrians” software simulates lifelike large-scale human activity.
Demetri Terzopoulos. Featured and quoted in December 2007 ZDNet Emerging Technology Trends in article “Autonomous Virtual Crowds.”
Demetri Terzopoulos. Bio in December 2008 WorldWide ElectroActive Polymers (Artificial Muscles) Newsletter.
Demetri Terzopoulos. Quoted in July 2008 Government Computer News, in the Tech
Reports’ story “Facing a Challenge.”
Demetri Terzopoulos. Featured and quoted in the Winter 07/08 Biomedical Computation
Review 4(1), in lead story entitled “Life in Motion: Simulation from Particles to People.”
Demetri Terzopoulos. Featured and quoted in March 2009 issue of The Economist, in
the Technology Quarterly article “Crowd Modelling: Model Behaviour.”
Demetri Terzopoulos. Research on the mathematics of design featured in April 2011 New
Scientist, in the Technology-News article “Rearranging the Furniture? Let Software Do It
For You.” Also featured on TMCnet.com in April, and in May, featured in the South China
Morning Post, the Oriental Daily, Apple Daily, and Sing Tao Daily.
Carlo Zaniolo. ACM SIGMOD 2012 Record interview for “Distinguished Profiles in
Databases.”
Other Honors
Judea Pearl. Honored by UCLA in March 2010 with an all-day workshop celebrating his
influential contributions to artificial intelligence and related science. The event coincided
with the 25th anniversary of Pearl’s introduction of the term “Bayesian network.”
Judea Pearl. 2013 appointment as Distinguished Visiting Professor at Technion ITT to
foster collaborative research in the areas of robotics and machine learning that will greatly
benefit both Technion and UCLA.
Amit Sahai. Record success at CRYPTO 2013, five research papers authored by Sahai
are accepted at this conference.
67
Jennifer Wortman Vaughan. Appointed Symantec Term Chair in Computer Science for
research in the realm of artificial intelligence that is at the forefront of computer science.
Lixia Zhang. Appointed Jonathan B. Postel Chair in Computer Science.
Lixia Zhang. 2013 election by ICANN (Internet Corporation for Assigned Names and
Numbers) to serve on its Identifier Technology Innovation panel.
Q
Start-up Companies
Jason Cong. His group developed xPilot, a novel platform-based high-level synthesis
(HLS) system to enable circuit designs from behavior descriptions such as C or C++ languages, as opposed to the traditional register-transfer level (RTL) hardware description
languages such as Verilog and VHDL. It can produce high-quality RTL designs that match
the quality of human RTL designs. The xPilot system was licensed to AutoESL Design
Technologies, co-founded by Prof. Cong and his PhD students in 2006. AutoESL’s highlevel synthesis tool was adopted by some of the world’s largest software and semiconductor
companies: Alcatel-Lucent, Broadcom, Intel, Lockheed-Martin, Microsoft, National Instruments, Qualcomm, Raytheon, and Xilinx. AutoESL was acquired by Xilinx, the largest
FPGA company worldwide, in Jan. 2011. The AutoESL tool was renamed as Vivado-HLS
and is now available to tens of thousands of Xilinx FPGA designers worldwide, becoming
the most widely deployed and used HLS tool in the EDA history.
Rafail Ostrovsky. Stealth Software Technologies is a company started at UCLA based on
Ostrovsky’s research and a patent.
Majid Sarrafzadeh. WANDA, Inc. is located in Palo Alto, CA. It develops remote health
monitoring systems (RMS), including a data-driven analytics engine that analyzes the data
collected from RMS. The company’s first product, the WANDA(tm) solution, is focused
on analyzing data from medical devices used for monitoring patients with chronic diseases
outside of the hospital setting to predict medical conditions or adverse medical events such
as hospital readmission, emergency visits, stroke, and death. The company has an ongoing
research collaboration with the Wireless Health Institute at UCLA.
Majid Sarrafzadeh. Medisens Wireless, Inc. is located in Santa Clara CA. It develops
wireless body monitoring systems which assess muscle and neuromotor functions as well as
applications for sleep disorders. It is introducing real-time, quantifiable, and objective assessment medical monitoring systems to empower cost containment in the healthcare industry.
The company has an ongoing research collaboration with the Wireless Health Institute at
UCLA.
Lixia Zhang. Three of her former students, Mohit Lad, Ricardo Oliveira, and Michael
Meisel, started ThousandEyes in 2010, http://www.thousandeyes.com. The company is
based on the research results of Zhang’s DARPA/DHS/NSF sponsored research on global
routing and DNS system monitoring, and was launched with NSF SBIR support.
68
ENGINEERING
Henry Samueli School of
Engineering and Applied Science
Birthplace of the Internet
4732 Boelter Hall
Los Angeles, CA 90095-1596
P: 310.825.3886 | F: 310.825.2273
www.cs.ucla.edu