Master's students specializing in advanced computing systems
MS (by Research) Student
Research work focuses on embodied AI for robotics with experience across robotic systems. Prior work spans robotic manipulation, Reinforcement Learning (RL), Imitation Learning (IL), and medical robotics, focusing on how embodied robotic agents integrate perception, semantics, communication, and control. Developed learning-based manipulation pipelines for assistive and healthcare settings using vision-language and 3D perception models, and designed multi-agent RL frameworks with attention-based communication for heterogeneous robotic systems. Earlier work on vision-based autonomy for medical robots, including monocular 3D reconstruction and real-time navigation for surgical robots. Current research explores leveraging foundation models within IL and RL frameworks for robotic navigation and manipulation tasks, enabling more robust and generalizable reasoning and control.
