Enming Liang

This is Enming Liang (梁恩明). Currently, I am a third-year Ph.D. student (2021-) in school of data science, City University of Hong Kong, supervised by Prof. Minghua Chen. I received my bachelor degree in School of Intelligent Systems Engineering from Sun Yat-sen University in 2020, supervised by Prof. Renxin Zhong. My research interests include machine learning for optimization, and its application for transportation and power systems.

[Curriculum Vitae]

Projects

---

Machine Learning for Constrained Optimization

NN Solution Feasibility

• Low Complexity Homeomorphic Projection to Ensure NN Solution Feasibility for Optimization over (Non-)Convex Set.
  Enming Liang, Minghua Chen, and Steven Low. ICML 2023.

Multi-valued Solution Mapping

• Generative Learning for Solving Non-Convex Problem with Multi-Valued Input-Solution Mapping.
  Enming Liang and Minghua Chen. ICLR 2024

Power Grid Application

• DeepOPF: Machine Learning for Solving Optimal Power Flow Problems

---

Reinforcement Learning for Transportation System

Ride-Sourcing Optimization

• An Integrated Reinforcement Learning and Centralized Programming Approach for Online Taxi Dispatching.
  Enming Liang, Kexin Wen, William Lam, Agachai Sumalee, and Renxin Zhong. IEEE TNNLS 2021.
• KDD CUP 2020: Learning to Dispatch and Reposition on a Mobility-on-Demand Platform
  Enming Liang (Solo winner. 2nd place for track 1. 5th place for track 2)

Traffic Signal Control

• OAM: An Option-Action Reinforcement Learning Framework for Universal Multi-Intersection Control
  Enming Liang, Zicheng Su, Chilin Fang, and Renxin Zhong. AAAI 2022.