Laboratory of Research in Optimization, Learning, and Energy

The laboratory of research in optimization, learning, and energy (ROLE) is focused on enabling trustworthy AI for societal-scale mission-critical systems such as power grids and smart cities. Towards this goal, we develop theoretical foundations and computational tools in the areas of optimization, control, and machine learning, with emphasis on various aspects of trust, including safety, security, reliability, explainability, and scalability. 

Research interests: control, machine learning, optimization, energy, cyber-physical systems

Research topics: reinforcement learning, robust learning on graphs, multi-agent learning and control, online learning, nonconvex optimization, robust control, cyber-physical system security


Ming Jin