Jie Feng

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 application to power systems.

Selected Publications (see all)

• Online Event-Triggered Switching for Frequency Control in Power Grids with Variable Inertia

  Jie Feng, Wenqi Cui, Jorge Cortés, Yuanyuan Shi

  IEEE Transactions on Power Systems, 2025.

• Combining Neural Networks and Symbolic Regression for Analytical Lyapunov Function Discovery

  Jie Feng, Haohan Zou, Yuanyuan Shi

  ICML Workshop on Foundations of Reinforcement Learning and Control, 2024

• Stability-Constrained Learning for Frequency Regulation in Power Grids with Variable Inertia

  Jie Feng, M. Muralidharan, R. Henriquez-Auba, P. Hidalgo-Gonzalez, Yuanyuan Shi

  IEEE Control Systems Letters, Vol. 8, pp. 994-999, 2024, presented at CDC 2024 in Milan

• Bridging Transient and Steady-State Performance in Voltage Control: A Reinforcement Learning Approach with Safe Gradient Flow

  Jie Feng, Wenqi Cui, Jorge Cortés, Yuanyuan Shi

  IEEE Control Systems Letters, presented at CDC 2023 in Singapore

• Stability Constrained Reinforcement Learning for Real-Time Voltage Control in Distribution Systems

  Jie Feng, Yuanyuan Shi, Guangyi Qu, Steven H. Low, Animashree Anandkumar, Adam Wierman

  IEEE Transactions on Control of Network Systems, 2023

• Graph Partitioning and Graph Neural Network Based Hierarchical Graph Matching for Graph Similarity Computation

  H. Xu, Z. Duan, Y. Wang, Jie Feng, R. Chen, Q. Zhang, Z. Xu

  Neurocomputing, 2021

• End-to-End Optimized Video Compression with MV-Residual Prediction

  X. Wu, Z. Zhang, Jie Feng, L. Zhou, J. Wu

  CVPR Workshop, 2020