Summary of skills

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  Seven plus years of coding experience in C/C++, Python, Java, Matlab
  
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  Experienced in software development GUIs and APIs including: Eclipse, Android SDK and Qt
  
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  Professional background in developing numerical analysis and simulation tools in MATLAB
  
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  Practical experience on HTML5 and web applications
  
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  Routinely working on Linux OS
  
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  Strong analytical, problem solving and communication skills
  
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  In-depth knowledge of distributed/cloud computing systems and power-grid systems
  
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  Rich experience in probabilistic modeling and mathematical analysis
  
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  Excellent team worker and fast-learner
  

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  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.
  
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  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
  
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  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
  

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  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
  
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  Successfully solved a tricky problem which is to analytically characterize the probability for the first-time consensus by creatively using conditioning method recursively
  

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  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.
  

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  Successfully derived asymptotic analysis on the proposed model by having carefully observed some of the imperceptible features when performing matrix operation
  

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  Be in charge of the Qatar National Research Fund (QNRF) project about Cloud Computing
  
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  Arranged routine Skype meetings between PIs from US universities and Qatar University
  
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  Helped in writing 6-month technical reports
  

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  Created and maintained the following two research-group websites
  

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  http://www.ece.unm.edu/lb/
  
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  http://powergrid.ece.unm.edu
  

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  Giving lectures for courses: ECE340 Probabilistic Methods in Engineering; ECE541 Probability and Stochastic Processes (Graduate course)
  
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  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.