Research Group

Our lab develops grid-inspired computing and learning methods for reliable, adaptive, and scalable power system operations. Grounded in grid physics, we explore how AI, quantum computing, and formal verification can harness the intrinsic characteristics of electric grids to address modern energy challenges.

Current research interests include:

• Grid-inspired quantum computing.
• Verifiable AI for power grids.
• Dynamic verification and stability analysis.
• Resilient operation of IBR-rich grids.

We are looking for self-motivated Ph.D. students with a strong background in power system dynamics and stability, and an interest in machine learning or quantum computing. Interested applicants are welcome to email me with your CV and transcripts.

Lab Members

Ph.D. Students

Master’s Students

Alumni

Our group is young and has no alumni yet.

Other Students Mentored