I am a fourth-year CS PhD student at Vanderbilt University, advised by Dr. Jie Ying Wu at MAPLE Lab, where we develop algorithms and systems for robot-assisted surgery. Since 2025, I have been doing my PhD research with the AI Research team at Intuitive Surgical, Inc. I expect to graduate in May 2027.

My research is in computer vision and robot learning for surgical robotics, focused on giving robots a better visual (2D) and spatial (3D) understanding of the scenes they act in. I work in three connected directions: (1) self-supervised, 3D-aware vision foundation models, such as DART, which teaches DINOv2-style models geometric structure from depth; (2) learning 3D scene dynamics from video, and using it to improve surgical robot policies on real hardware; and (3) photorealistic, physics-grounded synthetic data via neural and physically-based rendering, to train and evaluate 3D vision models in minimally invasive surgery.

Ultimately, my goal is to build embodied surgical AI systems that reduce surgeon workload and broaden access to high-quality care, especially in low-resource communities. My work has been supported by an NIH T32 training fellowship.

For collaboration, party invites, or any other inquiries, please contact me at john.j.han@vanderbilt.edu. I would love to get to know you and your work. Soli Deo Gloria!

Education

• PhD Computer Science, Vanderbilt University (Expected May 2027).
• MSE Robotics, Johns Hopkins University (2023).
• BS Electrical Engineering, Johns Hopkins University (2022).

Work Experience

• AI Research Intern (June 2025 - Current), Intuitive Surgical Inc.