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 aims to bridge 3D scene understanding and robot learning at scale specifically for surgical robots. I focus on two directions: (1) generating photorealistic, physics-grounded synthetic data to train and evaluate 3D vision models, and (2) developing multimodal learning methods, such as RGB-D pretraining, to capture both semantic and spatial/geometric information in endoscopic scenes. 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 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 2028).
• MSE Robotics, Johns Hopkins University (2023).
• BS Electrical Engineering, Johns Hopkins University (2022).

Work Experience

• AI Research Intern (June 2025 - March 2026), Intuitive Surgical Inc.