-
for understanding how AI-enabled control, optimization, and market design can support large-scale decarbonization, grid modernization, and the integration of distributed and flexible energy resources. Research topics
-
fellow to perform research on agentic AI, foundational modeling, optimization, and control of multiagent autonomous systems with an application in renewable energy and power grids, in addition to working
-
the project directors and collaborators to develop data-driven and economically grounded frameworks for understanding how AI-enabled control, optimization, and market design can support large-scale
-
cloud platforms for compute and storage. Version Control & CI/CD: Git, automated testing, deployment workflows. Experience with Linux systems, HPC, and distributed computing environments. Knowledge
-
fellow with a Ph.D. in electrical engineering, applied mathematics, or related field. Candidates will perform research on agentic AI, foundational modeling, optimization, and control of multiagent
-
integrates three synergistic research thrusts: Advanced thermal storage and sensing materials Intelligent, building-scale integration of sensing and control systems Cooperative, urban-scale energy management