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Zhuoyao Wang


935 Buena Vista Dr SE Apt E105, Albuquerque, NM 87106


  • 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


University of New Mexico Ph. D candidate in EE expected graduation in early Fall 2015

University of New Mexico M.S. in Electrical Engineering Dec. 2011

Jilin University, China B.E. in Electrical Engineering June 2008


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


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



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)


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.

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