Convex Q-Learning: Theory and Applications
Lu, F., 2023. Convex Q-Learning: Theory and Applications (Doctoral dissertation, University of Florida).
CV
Education
- Ph.D in Electrical and Computer Engineering, University of Florida, 2023
- M.S. in Electrical and Computer Engineering, University of Florida, 2019
- B.S. in Electrical Engineering and Automation, Nanjing University of Science and Technology, 2017
Work experience
- July. 2019 ~ Present: Postdoc Researcher
- University of California Santa Cruz
- Duties included: Research on Accelerating Wound Healing with Deep Reinforcement Learning
- Supervisor: Prof. Marcella Gomez
- Aug. 2019 ~ May. 2023: Graduate Research Assistant
- University of Florida
- Duties included: Research on Reinforcement Learning
- Supervisor: Prof. Sean Meyn
Skills
- Python, SQL, C/C++
- Machine/Deep Learning, Optimal Control
- Data Wrangling/Visualization
- Numpy, Pandas, Matplotlib, Seanborn
- Tableau
Publications
RetailNet: Enhancing Retails of Perishable Products with Multiple Selling Strategies via Pair-Wise Multi-Q Learning
Ma, Xiyao, Fan Lu, Xiajun Amy Pan, Yanlin Zhou, and Xiaolin Andy Li. "RetailNet: Enhancing Retails of Perishable Products with Multiple Selling Strategies via Pair-Wise Multi-Q Learning." (2019).
Modular Platooning and Formation Control
Zhou, Yanlin, George Pu, Fan Lu, Xiyao Ma, and Xiaolin Li. "Modular Platooning and Formation Control." (2019).
Adaptive leader-follower formation control and obstacle avoidance via deep reinforcement learning
Zhou, Yanlin, Fan Lu, George Pu, Xiyao Ma, Runhan Sun, Hsi-Yuan Chen, and Xiaolin Li. "Adaptive leader-follower formation control and obstacle avoidance via deep reinforcement learning." In 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 4273-4280. IEEE, 2019.
Zap Q-Learning With Nonlinear Function Approximation
Chen, Shuhang, Adithya M. Devraj, Fan Lu, Ana Busic, and Sean Meyn. "Zap Q-learning with nonlinear function approximation." Advances in Neural Information Processing Systems 33 (2020): 16879-16890.
Convex Q-Learning
Lu, Fan, Prashant G. Mehta, Sean P. Meyn, and Gergely Neu. "Convex Q-learning." In 2021 American Control Conference (ACC), pp. 4749-4756. IEEE, 2021.
Model-Free Characterizations of the Hamilton-Jacobi-Bellman Equation and Convex Q-Learning in Continuous Time
Lu, F., Mathias, J., Meyn, S. and Kalsi, K., 2022. Model-Free Characterizations of the Hamilton-Jacobi-Bellman Equation and Convex Q-Learning in Continuous Time. arXiv preprint arXiv:2210.08131.
Sufficient Exploration for Convex Q-learning
Lu, Fan, Prashant Mehta, Sean Meyn, and Gergely Neu. "Sufficient Exploration for Convex Q-learning." arXiv preprint arXiv:2210.09409 (2022).
Convex Analytic Theory for Convex Q-Learning
Lu, Fan, et al. "Convex analytic theory for convex Q-learning." 2022 IEEE 61st Conference on Decision and Control (CDC). IEEE, 2022.
Convex Q Learning in a Stochastic Environment: Extended Version
Lu, Fan, and Sean Meyn. "Convex Q Learning in a Stochastic Environment: Extended Version." arXiv preprint arXiv:2309.05105 (2023).
Enhancing Wound Healing via Deep Reinforcement Learning for Optimal Therapeutics
Lu Fan, Zlobina Ksenia, Rondoni Nicholas, Teymoori Sam and Gomez, Marcella. "Enhancing Wound Healing via Deep Reinforcement Learning for Optimal Therapeutics." In Royal Society Open Science (To Appear)
Talks
Convex Q-Learning: Theory and Applications
Talk at AM Seminar at the University of California Santa Cruz, Santa Cruz, CA
Accelerating Wound Healing using Deep Reinforcement Learning
Poster Presentation at Predictive Modeling in Biology and Medicine Conference, University of California, Riverside, CA