Scholar
Enming Liang
Google Scholar ID: Todfu6AAAAAJ
City University of Hong Kong
Citations & Impact
Citations
333
H-index
6
i10-index
6
Publications
16
Co-authors
10
list available
Publications
Resume (English only)
Academic Achievements
- Publications:
- - NeurIPS 2025: Fast Projection-Free Approach (without Optimization Oracle) for Optimization over Compact Convex Set
- - ICLR 2025 DeLTa Workshop: Gauge Flow Matching for Efficient Constrained Generative Modeling over General Convex Set
- - ICML 2025: Efficient Bisection Projection to Ensure Neural-Network Feasibility for Optimization over General Set
- - JMLR 2024: Homeomorphic Projection to Ensure NN Solution Feasibility for Constrained Optimization
- - ICML 2023: Low Complexity Homeomorphic Projection to Ensure NN Solution Feasibility for Optimization over (Non-)Convex Set
- - AAAI 2025: DFF: Decision-Focused Fine-tuning for Smarter Predict-then-Optimize with Limited Data
- - ICLR 2024: Generative Learning for Solving Non-Convex Problem with Multi-Valued Input-Solution Mapping
- - NeurIPS 2025 ScaleOPT workshop: On the Expressiveness of Graph Neural Network for Solving Second-Order Cone Programming
- - ICML 2024: Characterizing ResNet's Universal Approximation Capability
- - KDD CUP 2020: Learning to Dispatch and Reposition on a Mobility-on-Demand Platform, Solo, 2nd Place
- - IEEE TNNLS 2021: An Integrated Reinforcement Learning and Centralized Programming Approach for Online Taxi Dispatching
- - Awards: Outstanding Short Paper Award at ICLR 2025 DeLTa Workshop
Research Experience
- Currently a Research Assistant Professor at City University of Hong Kong (2025-); Member of DeepOPF, working with Prof. Steven Low, focusing on applying ML to power grid operation; Visited University of Cambridge, working with Prof. Srinivasan Keshav, focusing on power grid resilience under extreme weather; Contributed to AI for OPF tutorials in Climate Change AI summer school, working with Prof. Priya L. Donti; Working with DiDi, focusing on applying ML for improving efficiency of urban mobility-on-demand system; Worked as a research intern in MSRA (Beijing, 2022) and Huawei Noah's Ark Lab (Shenzhen, 2021), focusing on applying RL/ML to logistics and wireless optimization.
Education
- Ph.D. (2021-2024) at Department of Data Science, City University of Hong Kong, supervised by Prof. Minghua Chen; B.Eng. (2016-2020) at School of Intelligent Systems Engineering, Sun Yat-sen University, supervised by Prof. Renxin Zhong.
Background
- Research interests lie at the intersection of ML and Optimization, focusing on theoretically-grounded algorithms for efficient constrained optimization and generative modeling, with applications in mobility and energy systems.
Miscellany
- Personal Interests: Not provided
