Congratulations to Professor Enming LIANG of the Department of Data Science on receiving the 2026 ACM SIGEnergy Doctoral Dissertation Award Honorable Mention in recognition of his outstanding doctoral dissertation, Machine Learning for Constrained Optimization: Solution Feasibility and Multi-valued Solution Mapping.
Professor LIANG's research advances machine learning approaches for constrained optimization—problems prevalent in power systems, logistics, and operations research, where one must identify optimal solutions subject to hard constraints. Classical solvers often cannot meet the latency requirements of real-time applications, yet existing learning-based methods frequently produce constraint-violating outputs or fail to capture solution multiplicity. This thesis addresses these limitations by developing feasibility-guaranteed neural architectures and multi-solution learning frameworks, ensuring that AI-generated solutions are both vali and diverse. The resulting methods offer the speed of neural inference with the reliability demanded by safety-critical, time-sensitive applications.
Congratulations to Professor LIANG on this prestigious recognition and on this remarkable achievement in advancing machine learning for constrained optimization!
For more information, please visit the official announcement here.