Dr. Adam W. Gripton
PhD, MA, BA (Hons.)
4 Stewart Avenue, Currie EH14 5SQ -- Tel (07753) 458495
awgripton@hotmail.com – http://madpaint.org/awg
Current Position
May 2009 – Present
Postdoctoral Research Associate in Image Analysis
School of Mathematical and Computer Sciences; Institute of Petroleum Engineering
Heriot-Watt University, Edinburgh
Summary: My research for this project has involved quantification of statistical model
uncertainty, in order to study the relationship between observed noise and the shape of
the a posteriori density function of model parameters. We have developed relevant codes
for novel Monte Carlo techniques to allow application on a sponsor's external system.
Education and Qualifications
Doctor of Philosophy (Ph.D.)
October 2005 – May 2011
School of Engineering and Physical Sciences
Heriot-Watt University, Edinburgh
Thesis: Geometric margin domain description with instance-specific margins
Summary: My thesis concerns classification of abstract datapoints via the fitting of a
spherical domain about the dataset with minimal radius in a way that can deal with
missing data without arbitrary imputation and can operate rigorously in a kernel space.
Master of Arts, Honour School of Mathematics
Jesus College, University of Oxford
Grade achieved 2:1
September 2002 – July 2005
Elective units included: Probability, Mathematical Modelling, Applied Analysis, PDEs,
Fluid Dynamics, Financial Derivatives, Functional Programming and Data Structures
GCE 'A' Levels
Thorpe St. Andrew Sixth Form College, Norwich
Mathematics A, Physics A, German A
September 2000 – June 2002
Research Interests and Experience
My research interests are in the fields of data analysis, machine learning and statistical
parameter inference. My thesis project related particularly to classification, Bayesian
frameworks and kernel machines, with my postdoctoral research concerning uncertainty
quantification and Monte Carlo sampling techniques.
My PhD project was an EPSRC sponsored studentship supervised by Dr. Weiping Lu.
My studies gave me a grounding in classification methods, support vector machines and
kernel induced feature spaces, as well as requiring me to use techniques of Bayesian
inference to build classification machines to operate on a large, complex dataset provided
by an external sponsor. Through my research, I also developed vital skills in
programming, computational mathematics and algorithm design, particularly using the
Maple and Matlab platforms; I also developed my initiative and creativity skills in
finding and exploring novel theory for my thesis topic. Aside from experimental and
theoretical work, I was required to design and give presentations of my findings to groups
of delegates from the sponsor company and liaise with them in matters concerning
project direction.
My postdoctoral assignments have required the use of inference techniques, principally
based on Markov Chain and Hamiltonian Monte Carlo sampling. My studies have
required statistical expertise when dealing with Bayesian inference and autocorrelation of
samples; I have also produced codes for Riemann solvers in fluid dynamics for specific
application of our methods. More generally, my postdoctoral experience has honed my
skills of independent research and has allowed me the scope to guide the direction of
project work. My communication skills have been required through our collaboration
with two separate research groups, one with a theoretical development remit and the other
applying our methods to specific problems. The latter group has also required me to
formulate solutions to allow our developed codes to function properly on their systems.
In future, as well as developing my skills in the areas with which I am familiar, I hope to
direct the path of my research towards further areas of mathematics and computer science
that also interest me, including those of game theory, stochastic models, graph theory,
logistical systems and operational research.
Publications
A. Gripton and W. Lu, Kernel Domain Description with Incomplete Data: Using
Instance-Specific Margins to Avoid Imputation, International Conference on Pattern
Recognition, (2010), pp. 2921-2924
Thesis:
A. Gripton, Geometric Margin Domain Description with Instance Specific Margins,
PhD thesis, Heriot-Watt University, 2011.
Contributed discussion:
M. Girolami and B. Calderhead, Riemann Manifold Langevin and Hamiltonian
Monte Carlo Methods, Jnl. Royal Stat. Soc. B, 73/2 (2011) pp. 123-214
Paper review:
Principal Component Analysis with Interval Imputed missing values, Pattern
Recognition Letters (2010)
Teaching Experience
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I acted as laboratory co-ordinator for the Praxis Computing Skills unit for firstyear undergraduates for three years (2006-08). In addition to these duties, I
engaged in the development of this course alongside the course lecturers, and
acted in a supervisory role in my third year for the next year's co-ordinator.
I taught a course in Mathematical Physics to third-year undergraduates (2008-9),
organising and giving my own classes relating to the material, including sessions
of small-group and one-to-one tutoring where necessary, allowing the class to
engage with the subject matter and receiving extremely positive feedback.
My teaching duties have also included:
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Calculus B class, 1st year undergraduates, class-based tuition (03/10).
Foundation Physics, 1st year undergraduates (2008).
Exam invigilation and scribing for students with special needs (Early 07).
Conference and Seminar Attendance
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International Conference of Pattern Recognition (ICPR) 2010, Istanbul: Paper
proceedings and 3-hour poster discussion session (08/10)
Uncertainty in Computer Models (UCM) 2010, Sheffield: Attended inaugural
symposium hosted by MUCM research group (07/10)
British Applied Mathematics Colloquium (BAMC) 2010, Edinburgh (04/10)
Attendance at ERGO lectures in optimisation at University of Edinburgh (11/08)
Attendance at Royal Society of Edinburgh lectures (09/08)
Heriot-Watt University Research Conference (06/08)
MATLAB seminars at Heriot-Watt and Agilent Technologies, Edinburgh (03/08)
Presented poster of work completed at Heriot-Watt University Engineering and
Physical Sciences Poster Session (18/10/06)
Attendance at Bayesian Methods workshop, Heriot-Watt University (07/06)
GradSkills Conference "Research Futures", University of St. Andrews (06/06)
Attended week-long SUPA Graduate School in Data Analysis, University of
Glasgow (01/06)
Additional Skills
Training Seminars
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Participated in RDP Creativity and Innovation event (11/10)
RDP course in Thesis writing (2009)
UK GRAD School Week – PhD training course, Exeter University (07/07)
SUPA Entrepreneurship Course (05/07)
RDP courses in Plagiarism, Ethics and FOI (11/06)
UK GRAD course “How to be an Effective Researcher” (09/06)
General Skills
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Programming: I am skilled in the computational platforms of Maple and
MATLAB. Some of my MATLAB codes are available on the public File
Exchange. I am familiar with C++, FORTRAN and Haskell. I am currently
undertaking a course in JavaScript.
Scripting: I have a working knowledge of HTML and CSS, and can design a
simple web page to XHTML 1.1 standards. I am currently teaching myself PHP
and MySQL with a view to designing an online database application.
Computing: I am experienced with MS Windows including console based
commands; I have basic Unix/Linux skills and am experienced with IT problem
solving.
Editing: I am skilled in LaTeX typesetting and familiar with MetaPost vector
graphics. I am also experienced with Office applications including Word, Excel
and PowerPoint. My typing and proofreading skills are also of a high standard.
Languages: English (mother tongue), German (proficient), French (basic),
Japanese (basic).
Other: Full driving licence since January 2007.
References available on request