Computer Engineering Data

Hung Khanh Nguyen

**** ******* **** ** – Houston, TX 77047

H 281-***-**** • B ********@*****.***

̋ linkedin.com/in/hungkhanhnguyen • www.github.com/hungnk25 Summary

{ Ph.D in Electrical and Computer Engineering with extensive knowledge of large-scale mathematical optimization both in centralized and distributed computing.

{ Solid background in big data analytic and machine learning. Area of Expertise

{ Big Data: Machine Learning, Hadoop, MapReduce, HDFS, HBase, SQL, Hive, Splunk, Spark, Neo4j

{ Programming Languages: Java, C/C++, Python, Matlab, R, CUDA-GPU programming

{ Tools: Eclipse, MS Visual Studio, Matlab, Mathematica, LabVIEW, Github, TensorFlow, Linux

{ Optimization skills: Gurobi, Mosek, CPLEX, CVX, YALMIP, ADMM, Compressive Sensing, Parallel and Distributed Computing

Experience

Wireless Networking, Signal Processing and Security Lab University of Houston Research Assistant Sep. 2014– Now

{ Big Data Analytic for power system and wireless network:

- Analyzed large-scale smart meter data for customer clustering and profiling.

- Developed predictive models for pricing selection based on user’s energy consumption pattern.

- Proposed big data-scale parallel algorithms for optimal operations of large-scale power system and wireless network.

- Implemented the parallel and distributed algorithms using MapReduce framework to run on Hadoop cluster.

{ Built a Hadoop Computing Cluster with 8 computers at Wireless Networking, Signal Processing and Security Lab.

{ Image Recovery using Compressive Sensing:

- Developed a mathematical model to measure signal from sparse sampling using compressive sensing.

- Proposed an algorithm to recover the original image from the sparse sampling data. MicroSystem Engineering/Biotronik Houston, TX

Summer Intern Jun. 2016–Aug. 2016

{ Designed high-pass and low-pass Infinite Impluse Response (IIR) digital filters for new generation of bio-monitor devices.

{ Implemented IIR digital filters using fixed-point methodology and analyzed filter’s stability.

{ Proposed a novel verification methodology in frequency domain and wrote test cases to verify filters. 1/2

Education

University of Houston Houston, TX

Ph.D, Electrical and Computer Engineering, GPA: 3.7 9/2014–5/2017 Dissertation: Big Data Optimization for Distributed Resource Management in Smart Grid Kyung Hee University Seoul, South Korea

Master, Electrical and Computer Engineering 2010–2012 Ho Chi Minh City University of Technology Vietnam

Bachelor, Electrical and Electronic Engineering 2005–2010 Certifications

1. Machine Learning by Stanford University on Coursera 2. Machine Learning With Big Data by University of California, San Diego on Coursera 3. Introduction to Big Data by University of California, San Diego on Coursera 4. Introduction to Big Data Analytics by University of California, San Diego on Coursera 5. Hadoop Platform and Application Framework by University of California, San Diego 6. Graph Analytics for Big Data by University of California, San Diego on Coursera 7. The Data Scientist Toolbox by Johns Hopkins University on Coursera 8. Big Data - Capstone Project by University of California, San Diego on Coursera 9. R Programming by Johns Hopkins University on Coursera 10. Programming for Everybody (Python) by University of Michigan on Coursera Research and Publications

1. Hung Khanh Nguyen, Amin Khodaei, and Zhu Han, "Incentive Mechanism Design for Integrated Microgrids in Peak Ramp Minimization Problem," IEEE Transaction on Smart Grids. 2. Hung Khanh Nguyen, and Zhu Han, "Parallel and Distributed Resource Allocation with Minimum Tra c Disruption for Wireless Network Virtualization," IEEE Transaction on Communication. 3. Hung Khanh Nguyen, Amin Khodaei, and Zhu Han, "Distributed Algorithms for Peak Ramp Minimization Problem in Smart Grid," IEEE Smart Grid Communication Conference 2016, Australia. 4. Hung Khanh Nguyen, Amin Khodaei, and Zhu Han, "A Big Data Scale Algorithm for Optimal Scheduling of Integrated Microgrids," IEEE Transaction on Smart Grids. 5. Hung Khanh Nguyen, Hamed Mohsenian-Rad, Amin Khodaei, and Zhu Han, "Decentralized Reactive Power Compensation using Nash Bargaining Solution," IEEE Transaction on Smart Grids. 6. Hung Khanh Nguyen, Ju Bin Song, and Zhu Han, "Distributed Demand Side Management with Energy Storage in Smart Grid," IEEE Transaction on Parallel and Distributed Systems. 7. Hung Khanh Nguyen, Ju Bin Song, and Zhu Han, "Demand Side Management to Reduce Peak- to-Average Ratio using Game Theory in Smart Grid," in The 1st IEEE INFOCOM Workshop on Communications and Control for Sustainable Energy Systems, Florida, USA. 8. Hung Khanh Nguyen and Ju Bin Song, "Optimal Charging and Discharging for Multiple PHEVs with Demand Side Management in Vehicle-to-Building," Journal of Communications and Networks. 2/2

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