Jie Feng
PhD Candidate, University of California, San Diego
Advisor: Prof. Yuanyuan Shi
About Me
I am a PhD candidate at the University of California, San Diego, advised by Prof. Yuanyuan Shi. I am honored to be a UC‑National Lab In‑Residence Graduate Fellow, collaborating with Dr. Deepjyoti Deka at Los Alamos National Laboratory (LANL). My research focuses on reinforcement learning and control, with applications to modern power systems.
News
- May 2025: 🏛️ I will be visiting MIT this summer (June – September 2025).
- May 2025: 🎉 Our paper Analytical Lyapunov Function Discovery was accepted to ICML 2025.
- Dec 2024: 📢 Presented one paper at CDC 2024 in Milan, Italy.
- Apr 2024: 🏆 Awarded the UC National Lab In-Residence Fellowship.
Selected Publications (see all)
Analytical Lyapunov Function Discovery: An RL‑based Generative Approach
International Conference on Machine Learning (ICML), 2025.
Haohan is an undergraduate student I mentored.
Online Event‑Triggered Switching for Frequency Control in Power Grids with Variable Inertia
IEEE Transactions on Power Systems, 2025.
Combining Neural Networks and Symbolic Regression for Analytical Lyapunov Function Discovery
ICML Workshop on Foundations of Reinforcement Learning and Control, 2024.
Stability‑Constrained Learning for Frequency Regulation in Power Grids with Variable Inertia
IEEE Control Systems Letters, Vol. 8, pp. 994‑999, 2024 (presented at CDC 2024, Milan).
Bridging Transient and Steady‑State Performance in Voltage Control: A Reinforcement Learning Approach with Safe Gradient Flow
IEEE Control Systems Letters, presented at CDC 2023, Singapore.
Stability Constrained Reinforcement Learning for Decentralized Real-Time Voltage Control
IEEE Transactions on Control of Network Systems, 2023.
Graph Partitioning and Graph Neural Network‑Based Hierarchical Graph Matching for Graph Similarity Computation
Neurocomputing, 2021.
End‑to‑End Optimized Video Compression with MV‑Residual Prediction
CVPR Workshop, 2020.