- Signal Kinetics
I am an EECS Ph.D. student in the Signal Kinetics Group. I specialize in developing novel localization systems and algorithms that enable robots to sense and navigate in challenging environments. My research focuses on leveraging diverse sensing modalities, such as RF, acoustics, lidar, and vision, to solve complex localization problems in GPS-denied environments.
My expertise lies in robot localization, sensor-fusion, and control, with extensive experience in reinforcement learning for trajectory optimization and robot task control. I am passionate about in developing and deploying end-to-end robotic systems in real-world settings, which led me to co-found Nexuni, Co., an AI robotics startup that brings AI-powered robotic systems to industry clients.
Research Interests
- State-of-the-art Robotic Perception & Localization: Developing novel sensing and localization methods for robots to enable new capabilities in challenging environments.
- Sensor Fusion: Developing robust autonomous systems by fusing data from diverse sensor modalities, including Vision, LiDAR, RF, and Acoustics.
- Reinforcement Learning for Robotics: Developing RL-based methods for tasks like robot control, obstacle avoidance, and path planning.
Education
B.S. 2021 MIT
Electrical Engineering & Computer Science
M.Eng. 2023 MIT
Electrical Engineering & Computer Science