Advanced optimization, control, and machine learning for reliability and economically integrating large-scale distributed energy resources (DERs) into power system planning, operations, stability, and electricity markets.

With a strong background in complex adaptive systems, Garland's research blends mathematics, computer science, and social science to explore the relationship between our personal narratives and the information environment.

Adam studies the policy processes associated with public infrastructure investment, particularly the relationship between the design of the institutions responsible for water infrastructure and system sustainability.

Leixin Ma's career goal is a data-driven and physically consistent approach to modeling and designing programmable smart structures and robots, especially under complex fluid flow conditions.

Garg's research interests include control synthesis for multi-agent coordination using control theory and machine learning.