LU Renzhi is a lecturer of the Department of Automatic Control, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology.
His research interests include learning, optimization and control with applications to smart manufacturing and smart grid.
Academic Areas: Reinforcement learning, deep learning, smart manufacturing, smart grid
Academic Degrees
Ph.D in Hanyang University, Korea
Professional Experiences
2020- Member, Chinese Association of Automation (CAA)
2020- Member, China Computer Federation (CCF)
2020- Member, Chinese Society For Electrical Engineering (CSEE)
2018- Member, IEEE Membership
2018- Member, IEEE Computational Intelligence Society Membership
2018- Member, IEEE Industrial Electronics Society Membership
2018- Member, IEEE Power & Energy Society Membership
2020- Member, IEEE Control Systems Society Membership
Selected Publications
(1) Renzhi Lu; Ruichang Bai; Zhe Luo*; Junhui Jiang; Mingyang Sun; Hai-Tao Zhang; Deep Reinforcement Learning-based Demand Response for Smart Facilities Energy Management, IEEE Transactions on Industrial Electronics, 2021.
(2) Renzhi Lu; Yi-Chang Li*; Yuting Li; Junhui Jiang; Yuemin Ding*; Multi-agent deep reinforcement learning based demand response for discrete manufacturing systems energy management, Applied Energy, 2020, 276: 115473.
(3) Renzhi Lu; Seung Ho Hong*; Mengmeng Yu; Demand Response for Home Energy Management Using Reinforcement Learning and Artificial Neural Network, IEEE Transactions on Smart Grid, 2019, 10(6): 6629-6639.
(4) Renzhi Lu; Seung Ho Hong*; Incentive-based demand response for smart grid with reinforcement learning and deep neural network, Applied Energy, 2019, 236: 937-949.
(5) Renzhi Lu; Seung Ho Hong*; Xiongfeng Zhang; A Dynamic pricing demand response algorithm for smart grid: Reinforcement learning approach, Applied Energy, 2018, 220: 220-230.
Awards and Honors
2020 ESI, Highly Cited Papers
2020 Fondazione Eni Enrico Mattei, Eni Award Energy Frontiers Candidate
2020 Samsung, AI Researcher of the Year Candidate
2020 Applied Energy, Highly Cited Paper Awards
2019 Hanyang University, Excellent Doctoral Thesis
2018 Education Office of the Embassy of the People’s republic of China in Korea, Outstanding Student
Course Taught
For Undergraduates:
Python programming, Data science and technology
For Graduates:
Reinforcement learning
Research Projects
1.National Natural Science Foundation of China, 62003143, 2021-2023, PI
2.Fundamental Research Funds for the Central Universities, HUST2020kfyXJJS084, 2020-2022, PI
3.State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, LAPS21006, 2021-2022, PI
4.State Key Laboratory of Industrial Control Technology, ICT2021B32, 2021, PI
5.Key Laboratory of Industrial Internet of Things and Networked Control, 2020FF02, 2021-2023, PI
6.National Natural Science Foundation of China, 62073148, 2021-2024, Participator
7.National Research Foundation of Korea through the Framework of International Cooperation Programs (Korea-China), NRF-2018K1A3A1A61026320, 2018-2020, Participator
8.National Research Foundation of Korea through the Framework of International Cooperation Programs (Korea-China), NRF-2016K2A9A2A11938310, 2016-2018, Participator
