I am a third-year CS PhD student at Vanderbilt University, advised by Dr. Jie Ying Wu at MAPLE Labs, where we develop algorithms and systems to enhance robot-assisted surgeries. My research interests are in computer vision applied to surgical robotics, ultimately to improve visual (2D) and spatial (3D) understanding for surgical policy learning. My focus is on three directions: (1) generating photorealistic, physics-grounded synthetic data to train and evaluate 3D vision models in minimally invasive surgery, (2) self-supervised learning for visual and spatial understanding (i.e., VFMs), and (3) using these findings for improved surgical robot policy learning. Ultimately, my goal is to build embodied surgical AI systems that reduce surgeon workload and democratize access to high-quality care, especially in low-resource communities. I am currently working on the AI Research team at Intuitive Surgical, Inc. and have 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 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.