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About him

Xiang Huo received the B.S. degree in Automation and the M.S. degree in Control Science and Engineering from Harbin Institute of Technology, Harbin, China, in 2017 and 2019, respectively. He obtained his Ph.D. from the Department of Electrical and Computer Engineering at the University of Utah at the University of Utah in 2024, supervised by Prof. Mingxi Liu. Currently, he is an Assistant Professor at the Department of Electrical and Computer Engineering at Hampton University. He was a Postdoc Associate affiliated with the Department of Electrical and Computer Engineering at Texas A&M University, working with Prof. Katherine Davis. During summer 2022, he was a research intern at the Grid Interactive Controls Group, Oak Ridge National Laboratory worked on the scalable control of grid-interactive buildings. His research interests include multi-agent optimization, reinforcement learning, privacy and security in cyber-physical power and energy systems. His research is supported by the U.S. Department of Energy and the National Science Foundation.

Research

Power systems are large-scale, highly interconnected infrastructures integrating generation, transmission, and distribution systems that deliver electricity to modern society. These systems are inherently cyber-physical due to their interdependent operation on continuous data exchange across sensing, communication, and control layers. The growing scale and interconnection of cyber and physical components introduce significant operational challenges, particularly evident in the surge of coordinated cyber-physical threats. In 2024, cyberattacks on US utilities increased 70%.

To deal with such challenges, my research pioneers control, optimization, and machine learning techniques that are secure, scalable, and testable for practical cyber-physical power system applications. The research goal is to design cybersecure, privacy-aware, and resilient cyber-physical energy management systems that can withstand and adapt to evolving cyber-physical threats while meeting future energy needs. My prior and current work can be summarized into three major thrust: (1) privacy and security enhancement for cyber-physical systems, (2) scalable control, optimization, and machine learning, and (3) optimal power system restoration and recovery.

Teaching

Courses taught include Introduction to Engineering, Introduction to Power Systems and Analysis, Energy Conversion, Control Systems, and ECE Laboratory (Electromechanics and Control Systems) at Hampton University. Additionally, teaching assistantships in Introduction to Electric Power Engineering and Introduction to Feedback Systems at the University of Utah.

News

• Paper accepted for CDC2023! Our recent paper titled “On privacy preservation of electric vehicle charging control via state obfuscation,” will be presented at the CDC 2023 | Dec. 13 – Dec. 15 | Singapore!
• Our proposal wins the Runner-Up of the Wilkes Center Student Innovation Prize (10K), titled “Decarbonize the Diné: A Prefabricated Solar-Driven Communal Solution with Passive Survivability,” at the Wilkes Center for Climate Science & Policy!
• Incoming presentation at PES2023! A poster regarding “Scalable and Privacy-Preserving Distributed Energy Resource Control Over Cloud-Edge Computing” at the PES 2023 | July 16 – July 20 | Orlando, Florida.
• Incoming presentation at ACC23! The previous published article “Two-Level Decentralized-Centralized Control of Distributed Energy Resources in Grid‐Interactive Efficient Buildings.” will be presented at the ACC 2023 | May 31 – June 2 | San Diego.
• New paper! Available at “Privacy-Preserving Distributed Energy Resource Control with Decentralized Cloud Computing,” arXiv.
• Research Intern at Grid Interactive Controls Group, Oak Ridge National Laboratory, a wonderful experience! Jun. 2022 – Sept. 2022.