Ming Jin I am an assistant professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. I am also affiliated with the Power and Energy Center, Autonomy and Robotics @ VT, and a core faculty of the Sanghani Center for Artificial Intelligence and Data Analytics. I work on trustworthy AI, safe reinforcement learning, foundation models, with applications for power systems, recommender systems, and control systems.

I received my PhD in Electrical Engineering and Computer Science from UC Berkeley and BEng (honors) in Electronic and Computer Engineering from the Hong Kong University of Science and Technology. I was a postdoc in Industrial Engineering and Operations Research at UC Berkeley.

Research interests

Trustworthy AI

Develop data-driven technology that can be trusted to do the critical work

CPS Security

Protect the critical infrastructure against cyber and physical attacks

Human-centric Technology

Design methods that respect human-centric needs and values

Future Energy Systems

Ensure sustainable and reliable access to power and energy for society

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Services and Outreach

• AC/SPC of ICML 2024, AAAI 2025
• Associate Editor of IEEE Systems Journal
• Safe Reinforcement Learning Tutorial @ IJCAI 2024 (Slides)
• Trustworthy Interactive Decision-Making with Foundation Models Workshop @ IJCAI 2024
• Safe RL for power systems Tutorial and Workshop @ SmartGridComm 2024 (Slides)
• Distributed Control and Machine Learning for Power Systems Tutorial @ SmartGridComm 2024 (Slides)
• Safe Reinforcement Learning Online Seminar (Website)

Selected Awards

• 1st Place Winner of the 2021 CityLearn Challenge (2021)
• Siebel Scholar (class of 2018)
• Best paper award, Building and Environment (2018)
• Best paper runner-up award at EAI MobiQuitous (2016)
• Best paper award at UBICOMM (2015)