I am a Ph.D. student in Computer Science at Johns Hopkins University, working at the intersection of computer vision and medical robotics. My goal is to make minimally invasive surgery safer and more autonomous by enabling machines to reliably perceive and navigate inside the human body from ordinary endoscopic video, turning what a camera sees into a coherent understanding of the surgical scene.

Specifically, I develop geometry-aware, domain-robust visual representations that transform monocular endoscopic video into structured, temporally-consistent state estimates for navigation and guidance across procedures such as bronchoscopy, arthroscopy, and sinus surgery. My work spans robust visual SLAM, foundation model representations for pose estimation, and simulation for training and automation, building toward scalable endoscopic digital twins for robot-assisted and automated intervention. Previously, I obtained my M.S.E. in Robotics from Johns Hopkins University in 2023.