Research experience
Work across autonomy, planning, and learning.
Research and training spanning scalable multi-agent systems, robot control, and data-driven decision-making.
-
ML/AI Research Intern
Research internship in ML/AI; project details are not public.
-
Research Assistant · LEADCAT Lab
Research on scalable multi-agent planning, resource-constrained autonomy, and robot navigation under partial observability.
-
Machine Learning Intern
Machine learning internship in Palo Alto, California.
-
Research Intern · GRASP Lab
Explored neural ODE and Lie algebra methods for robotic control and dynamics prediction.
-
B.Tech. (Honors), Aerospace Engineering · Minor in Systems and Controls Engineering
Undergraduate training in stochastic control, reinforcement learning, navigation, and motion planning.