I work to enable co-adaptive artificial and mechanical intelligence for scalable and reliable robot systems in resource-constrained, unpredictable, and adversarial environments. Such systems are found in defense, disaster response, and smart cities in robot applications such as situational awareness, autonomous driving, and infrastructure inspection and maintenance. To this end, I work at the intersection of control, robotics, and machine learning, contributing (i) to artificial intelligence, resource-, failure-, and risk-aware learning and optimization for perception, coordination, and control, and (ii) to mechanical intelligence, morphable aerial vehicles for extreme mobility, reliability, and efficiency.
I received my Ph.D. in Electrical and Systems Engineering at the University of Pennsylvania, along with an MA in Statistics and an MS in Electrical Engineering. I was a postdoc and research scientist at the Massachusetts Institute of Technology (MIT), AeroAstro and LIDS. I have been fortunate to receive an NSF CAREER Award, an Army Research Office Early Career Program Award (ARO YIP), the Best Paper Award in Robot Vision at the 2020 IEEE International Conference on Robotics and Automation (ICRA), an Honorable Mention from the 2020 IEEE Robotics and Automation Letters (RA-L), and a Best Student Paper Finalist Award at the 2017 IEEE Conference in Decision and Control (CDC).