Autonomous agents are transforming both robotic and cyber-physical systems through their ability to amplify human capability and coordinate complex activities at scales and speeds beyond direct human supervision. In robotic domains, multi-agent coordination enables teams of autonomous vehicles, drones, and manipulators to perform tasks that exceed the capacity of any individual system. In cyber-physical systems, distributed autonomous processes can manage critical infrastructure, optimize resource flows, and adapt intelligently to dynamic environments. However, the realization of these capabilities hinges on ensuring their safety and reliability. Thus, as our technological ecosystems grow in complexity, so does our need for explainable frameworks that can facilitate autonomous collaboration reliably, intelligently, and safely.

With an emphasis on networked control systems and safety-critical control, my research focuses on bridging the gap between theory and application. I strive for research that advances our basic understanding of core concepts, where my past and current work include applications across multiple domains that build toward designing explainable, safe, and collaborative control frameworks for dynamic and networked autonomous systems.

Two examples of trajectories for an 8-agent system where the star shows each agent's goal. On the left, all agents are assigned equal importance values, whereas on the right, we assign the greatest importance to the blue and orange agents.