Jie Feng - PhD student, UC San DiegoI am a PhD Candidate in University of California, San Diego. My advisor is Prof. Yuanyuan Shi. I am fortunate to be awarded as a UC-National Lab In-Residence Graduate Fellow and work in Los Alamos National Laboratory (LANL) with Dr. Deepjyoti Deka. I am interested in AI algorithms with stability constraints. Currently I am working on stability constrained voltage control problems with reinforcement learning algorithms.
Personal | Vitæ | Google Scholar | Twitter | Github
| LCSS, presentation in CDC 2023 | Bridging Transient and Steady-State Performance in Voltage Control: A Reinforcement Learning Approach with Safe Gradient Flow. | | J Feng, W Cui, J Cortes, Y Shi | | TCNS, 2023 | Stability Constrained Reinforcement Learning for Real-Time Voltage Control in Distribution Systems. | | J Feng, Y Shi, G Qu, S H. Low, A Anandkumar, A Wierman | | Neurocomputing, 2021 | Graph partitioning and graph neural network based hierarchical graph matching for graph similarity computation. | | H Xu, Z Duan, Y Wang, J Feng, R Chen, Q Zhang, Z Xu | | CVPR Workshop, 2020 | End-to-end Optimized Video Compression with MV-Residual Prediction. | | XJ Wu, Z Zhang, J Feng, L Zhou, J Wu |
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