Enming Liang

Currently, I am a Research Assistant Professor at City University of Hong Kong. My research interests include Machine Learning for Constrained Optimization, Generative Models, and its application for Mobility, Energy, and Climate.

I received Ph.D. (2021-2024) at Department of Data Science, City University of Hong Kong, supervised by Prof. Minghua Chen. I received bachelor degree (2016-2020) at School of Intelligent Systems Engineering, Sun Yat-sen University. supervised by Prof. Renxin Zhong.

I have been a member of the DeepOPF team, working with Prof. Steven Low. I had visited department of CST, University of Cambridge, supervised by Prof. Srinivasan Keshav. I had contributed to tutorials for the Climate Change AI summer school, working with Prof. Priya L. Donti.

I had worked as a research intern in MSRA (Beijing, 2022), Huawei Noah's Ark Lab (Shenzhen, 2021), and DiDi-SYSU Research Program (Guangzhou, 2020).

We have 25/26 PhD/RA positions, please mail your CV if interested.


Learning & Approximation Theory
Decision-Focused Learning
Decision-Focused Fine-tuning
DFF: Decision-Focused Fine-tuning for Smarter Predict-then-Optimize with Limited Data.
Jiaqi Yang*, Enming Liang*, Zicheng Su, Zhichao Zou, Peng Zhen, Jiecheng Guo, Kun An, Wanjing Ma.
AAAI 2025
Oral. Deployed in DiDi Chuxing.
Ride-Sourcing Optimization
Power Grid Operation
AI for OPF Tutorial
AI for Optimal Power Flow Tutorial
Enming Liang, Priya L. Donti, and Minghua Chen.
Climate Change AI Summer School 2024
Chance-Constrained AC-OPF
Solving Chance-Constrained AC-OPF Problems by Neural Network with Bisection-based Projection.
Enming Liang*, Min Zhou*, Jiawei Zhao, and Minghua Chen.
ACM E-energy 2025, EnergySP workshop
Invited Paper.

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