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 AI algorithms with stability constraints, particularly in stability-constrained voltage control using reinforcement learning techniques.

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

  arXiv preprint, 2024, submitted to Transactions on Power Systems

• 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, to be 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