Meiyi Li

I am Meiyi Li, a Ph.D. candidate in Civil, Architectural, and Environmental Engineering at The University of Texas at Austin, advised by Prof. Javad Mohammadi. I’m on the job market and excited to find my next opportunity!

My research focuses on machine learning and optimization for decision-making under uncertainty in large-scale systems such as power grids, sensor networks, smart cities, and mobility infrastructures. I explore multi-agent methods and cyber-physical infrastructures, with an emphasis on developing trustworthy and sustainable AI.

I am honored to have collaborated with Prof. Soheil Kolouri, Prof. Kyri Baker, and Prof. Constance Crozier on projects including trustworthy AI, distributed optimization, and the ARPA-E Grid Optimization Competition.

Before joining UT Austin, I was a Ph.D. student in Electrical and Computer Engineering at Carnegie Mellon University, where I worked with Prof. Soummya Kar and Prof. Javad Mohammadi on distributed optimization for energy markets.

I earned both my B.S. and M.S. in Electrical Engineering from Shanghai Jiao Tong University, as part of the Outstanding Engineers Honor Class, under the supervision of Prof. Nengling Tai and Prof. Wentao Huang.

Outside of research, I enjoy hiking and swimming.

Hiking and swimming

🔬 Research Interests

Machine learning-driven optimization and trustworthy AI
Power dispatch and renewable integration
Distributed energy resource (DER) coordination
Risk-aware and uncertainty-driven optimization
Smart buildings and HVAC optimization
Carbon-aware and sustainable computing
Energy–mobility co-optimization (EV fleets, charging, autonomous vehicles)
Cybersecurity and adversarial robustness in power systems

Meiyi Li

Meiyi Li

🔬 Research Interests

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