Hepeng Li

Hepeng Li

Assistant Professor
hli@bradley.edu

Ph.D., Electrical Engineering, University of Rhode Island, USA
M.S., Control Theory and Control Engineering, Northeastern University, China
B.S., Information and Computing Science, Northeastern University, China

BIOGRAPHY
Dr. Hepeng Li is an assistant professor with the Department of Computer Science and Information Systems at Bradley University, Peoria, IL. He received his Ph.D. degree in Electrical Engineering from University of Rhode Island, Kingston, RI, USA, in 2023. He received his master’s degree in Control Theory and Control Engineering and B.S. degree in Information and Computing Science from Northeastern University of China in 2012 and 2009, respectively. From 2012-2018, he worked as an assistant research fellow at Shenyang Institute of Automation, Chinese Academy of Science, China. From 2018-2019, he worked as a senior data scientist in Kanzhun Ltd. (NASDAQ: BZ), Beijing, China.

Dr. Li serves as a member of IEEE Computational Intelligence Society (CIS) Adaptive Dynamic Programming and Reinforcement Learning (ADPRL) Technical Committee (2023-Present). He served as the session chair of an oral presentation session on Reinforcement Learning at the International Conference on Machine Learning 2022 (ICML'22). He was also the assistant to the editor-in-chief of IEEE Transactions on Neural Networks and Learning Systems (TNNLS) in 2021.

TEACHING

  • CS 101 – Introduction to Programming
  • CS 560 – Fundamentals of Data Science

SCHOLARSHIP
Current research interests lie in Reinforcement Learning, Multi-Agent Systems, Distributed Optimization, and their applications in Smart Grids, Robotics, and Cyber-Physical Systems.

  • Reinforcement Learning: Policy Optimization, Off-Policy Algorithms, Safe Reinforcement Learning
  • Multi-Agent Systems: Games Theory, Distributed Optimization, Federated Reinforcement Learning
  • Robotics and Cyber-Physical Systems: Adaptive Learning, Path Planning, Multi-Agent Cooperation

Selected Publications

  1. Hepeng Liand Haibo He, “Multiagent Trust Region Policy Optimization,” in IEEE Trans. on Neural Networks and Learning Systems (TNNLS). DOI: 10.1109/TNNLS.2023.3265358
  2. Hepeng Li, Xiangnan Zhong and Haibo He, "An Improved Trust-Region Method for Off-Policy Deep Reinforcement Learning," 2023 International Joint Conference on Neural Networks (IJCNN), Gold Coast, Australia, 2023, pp. 1-8, doi: 10.1109/IJCNN54540.2023.10191837. (Oral Presentation)
  3. Hepeng Li, Nicholas Clavette and Haibo He, “An Analytical Update Rule for General Policy Optimization,” in Proceedings of the 39thInternational Conference on Machine Learning (ICML’22), Baltimore, Maryland, USA, July 17-23, 2022. (Long Oral Presentation)
  4. Hepeng Liand Haibo He, “Learning to Operate Distribution Networks with Safe Deep Reinforcement Learning,” in IEEE Trans. on Smart Grid (TSG), vol. 13, no. 3, pp. 1860-1872, May 2022.
  5. Hepeng Li, Zhiqiang Wan, and Haibo He, “Online Microgrid Energy Management Based on Safe Deep Reinforcement Learning,”2021 IEEE Symposium Series on Computational Intelligence (SSCI’21), Orlando, FL, USA, December 5-7, 2021. (Oral Presentation)
  6. Hepeng Li, Zhenhua Wang and Haibo He, “Distributed Volt-VAR Optimization based on Multi-Agent Deep Reinforcement Learning,”2021 International Joint Conference on Neural Networks (IJCNN’21), Shenzhen, China, July 18-22, 2021. (Oral Presentation)
  7. Hepeng Li, Zhiqiang Wan and Haibo He, “Constrained EV Charging Scheduling Based on Safe Deep Reinforcement Learning,” in IEEE Trans. on Smart Grid (TSG), vol. 11, no. 3, pp. 2427-2439, May 2020.

SERVICE
IEEE CIS ADP and Reinforcement Learning Technical Committee, 2023 - present

Session Chair of Reinforcement Learning, International Conference on Machine Learning (ICML'22), Baltimore, MA, US, Jul. 17 - 23, 2022

Assistant to the Editor-in-Chief, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021

Journals & Conference Reviewer:

  • IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
  • IEEE Transactions on Artificial Intelligence (TAI)
  • IEEE Transactions on Smart Grid (TSG)
  • IEEE Transactions on Power System (TPS)
  • IEEE Transactions on Sustainable Energy (TSE)
  • IEEE Transactions on Green Communications and Networking (TGCN)
  • IEEE Transactions on Semiconductor Manufacturing (TSM)
  • IEEE Internet of Thing Journal (IoT-J)
  • ACM Transactions on Internet of Things (TIOT)
  • Journal of Modern Power Systems and Clean Energy (MPCE)
  • Applied Energy (APEN)
  • International Journal of Electrical Power and Energy Systems (JEPES)
  • Energy Conversion and Economics (ECE)
  • International Conference on Machine Learning (ICML’22)
  • IEEE Symposium Series on Computational Intelligence (SSCI’22)
  • IEEE Power & Energy Society General Meeting (PESGM’22)
  • IEEE International Joint Conference on Neural Networks (IJCNN’21)

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