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

Real-time multi-resource jointed scheduling of container terminals with uncertainties using a reinforcement learning approach. - Renxin Zhong; Kexin Wen; Chilin Fang; Enming Liang (ASCC, 2022)

An Integrated Reinforcement Learning and Centralized Programming Approach for Online Taxi Dispatching. - Enming Liang; Kexin Wen; William H. K. Lam; Agachai Sumalee; Renxin Zhong (IEEE Trans. Neural Networks Learn. Syst., 2022)

Low Complexity Homeomorphic Projection to Ensure Neural-Network Solution Feasibility for Optimization over (Non-)Convex Set. - Enming Liang; Minghua Chen 001; Steven H. Low (ICML, 2023)

An Approximate Dynamic Programming Approach to Vehicle Dispatching and Relocation Using Time-Dependent Travel Times. - Yunping Huang; Nan Zheng; Enming Liang; Shu-Chien Hsu; Renxin Zhong (ITSC, 2023)

Solving Chance-Constrained AC-OPF Problems by Neural Network with Probabilistic Homeomorphic Projection. - Enming Liang (BuildSys, 2024)

Generative Learning for Solving Non-Convex Problem with Multi-Valued Input-Solution Mapping. - Enming Liang; Minghua Chen 001 (ICLR, 2024)

Characterizing ResNet's Universal Approximation Capability. - Chenghao Liu; Enming Liang; Minghua Chen 001 (ICML, 2024)

DFF: Decision-Focused Fine-Tuning for Smarter Predict-Then-Optimize with Limited Data. - Jiaqi Yang; Enming Liang; Zicheng Su; Zhichao Zou; Peng Zhen 001; Jiecheng Guo; Wanjing Ma; Kun An (AAAI, 2025)

Solving Chance-Constrained AC-OPF Problem by Neural Network with Bisection-based Projection. - Enming Liang; Min Zhou; Jiawei Zhao; Minghua Chen 001 (e-Energy, 2025)