Speaker
Enming Liang
Speaker Bio
Dr. Enming Liang is a Research Assistant Professor in the College of Computing at City University of Hong Kong. His research lies at the intersection of machine learning, constrained optimization, and generative models, with a focus on ML-driven optimization and constrained generative modeling for safety- and physics-constrained systems. He received his Ph.D. in Data Science from City University of Hong Kong in 2024 and his B.Eng. in Intelligent Systems Engineering from Sun Yat-sen University in 2020. He has published in top-tier venues including JMLR, ICML, NeurIPS, ICLR, and AAAI, with multiple oral and spotlight presentations, and has received distinctions such as an outstanding short paper award at the ICLR DeLTa Workshop and 2nd place in the ACM KDD Cup. His work has practical applications spanning power systems, transportation networks, and climate resilience.
Talks at this conference:
| 15:35 | Homeomorphism Methods for Efficient Learning and Optimization with Hard Constraints |