Our Research

Advancing methods in computer vision, scene understanding, medical image analysis, and language modeling to help machines interpret complex clinical environments with depth, accuracy, and context-awareness.

People: Lalith, Hao, Yiqing, Xinrui, Benjamin, Jan, Hongchao, Han

Designing collaborative systems that support and amplify human expertise—from immersive surgical training to real-time decision support—focused on building trust through intuitive, interpretable interfaces, digital twins, and adaptive environments.

People: Catalina, Jasmine, Hongchao, Blanca

We develop robotic and semi-autonomous systems to enhance human expertise in the operating room. By integrating perception, planning, and manipulation, our goal is to build intelligent tools that support surgical skill, improve precision, and expand what’s possible in high-stakes environments.

People: Lalith, Benjamin, Jan, Han, Blanca, Grayson

Translating research into clinical practice through rigorous validation, robust system design, and real-world testing—ensuring that our technologies meet the demands of surgical workflows and patient safety. We also emphasize dataset transparency and synthetic data strategies to identify and mitigate bias in algorithm development.

People: Nathan, Mitchell, Grayson