Zhuoyao Wang
(505)750-2518
wzy0791@gmail.com
935 Buena Vista Dr SE Apt E105, Albuquerque, NM 87106
SUMMARY OF SKILLS
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Seven plus years of coding experience in C/C++, Python, Java, Matlab
Experienced in software development GUIs and APIs including: Eclipse, Android SDK and Qt
Professional background in developing numerical analysis and simulation tools in MATLAB
Practical experience on HTML5 and web applications
Routinely working on Linux OS
Strong analytical, problem solving and communication skills
In-depth knowledge of distributed/cloud computing systems and power-grid systems
Rich experience in probabilistic modeling and mathematical analysis
Excellent team worker and fast-learner
EDUCATION
University of New Mexico
University of New Mexico
Jilin University, China
Ph. D candidate in EE
M.S. in Electrical Engineering
B.E. in Electrical Engineering
expected graduation in early Fall 2015
Dec. 2011
June 2008
RESEARCH
Cloud Computing
 Developed a probabilistic multi-tenant model for characterizing performance of a group of workloads (for
example, multi-tier applications) serving on modern cloud platforms, such as Amazon AWS EC2.
 The proposed model is of great benefit for cloud brokers or small-to-mid enterprises to operate and manage
their own cloud services by giving the provisioning balance between performance and pricing
 Proposed a greedy heuristic resource allocation (or load balancing) algorithm for achieving best
computational performance in cloud computing environment with rigorous proof of the optimality
Resource Allocation in Distributed Systems
 Developed and implemented a lattice algorithm, which highly outperformed the previous algorithms in
terms of idea clarity, code readability and computational complexity, for solving problems of coupled
difference equations
 Successfully solved a tricky problem which is to analytically characterize the probability for the first-time
consensus by creatively using conditioning method recursively
Cascading Failures in Power Grids
 Built a novel continuous-time Markov chain model to understand and approximate cascading failures in
power grids. The model embeds the details of physics in power but is still analytical and linear in complexity.
 Successfully derived asymptotic analysis on the proposed model by having carefully observed some of the
imperceptible features when performing matrix operation
EXPERIENCE
Invited Researcher
Qatar University, Doha, Qatar
May 2013 - Sep. 2013
 Be in charge of the Qatar National Research Fund (QNRF) project about Cloud Computing
 Arranged routine Skype meetings between PIs from US universities and Qatar University
 Helped in writing 6-month technical reports
Research Group Websites Creator and Maintainer
University of New Mexico
 Created and maintained the following two research-group websites
 http://www.ece.unm.edu/lb/
 http://powergrid.ece.unm.edu
Teaching and Teaching Assistant
University of New Mexico
 Giving lectures for courses: ECE340 Probabilistic Methods in Engineering; ECE541 Probability and
Stochastic Processes (Graduate course)
 TA for ECE131 Programing Fundamentals (i.e., Programming in C)
SELECTED PUBLICATIONS
1. Z. Wang, M. M. Hayat, Nasir Ghani and Khaled B. Shaban,“A probabilistic multi-tenant model for
virtual machine mapping in cloud systems,” in Proc. of The Third IEEE International Conference on
Cloud Networking to be held in Luxemburg, October 8-10, 2014.
2. Z. Wang, M. M. Hayat, M. Rahnamay-Naeini, Y. Mostofi, and J. E. Pezoa, “Consensus-based Estimation
Protocol for Decentralized Dynamic Load Balancing over Partially Connected Networks,” in Proc. of
The 50th IEEE Conference on Decision and Control and European Control Conference (IEEE CDC-ECC
2011) in Orlando, Florida, December 12-15, 2011.
3. M. Rahnamay-Naeini, Z. Wang, N. Ghani, A. Mammoli, and M. M. Hayat, “Stochastic Analysis of
Cascading Failure Dynamics in Power Grids”, IEEE Transactions on Power Systems, vol.29, no.4,
pp.1767-1779, July 2014.