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Summary: I am a postdoc at Johns Hopkins University working under the guidance of Axel Krieger and Chelsea Finn. My research involves combining machine learning and robotics to develop autonomous systems, particularly for robotic surgery.

During my PhD, I focused on developing autonomous surgical workflows for eye surgery under the guidance of Marin Kobilarov and Iulian Iordachita. Our notable achievements include pioneering advancements in automating  subretinal injection and retinal vein cannulation. Previously, I interned at Zoox (self-driving company owned by Amazon) in the planning & controls and prediction team. 

Feel free to reach out to me if you'd like to chat: jkim447@jhu.edu

Education


Experience

Selected Publications

SRT-H: A Hierarchical Framework for Autonomous Surgery via Language Conditioned Imitation Learning

Ji Woong Kim, Juo-Tung Chen, Pascal Hansen, Lucy Shi, Antony Goldenberg, Samuel Schmidgall, Paul Scheikl, Anton Deguet, Brandon White, De Ru Tsai, Richard Cha, Jeffrey Jopling, Chelsea Finn, Axel Krieger

Under review @ Science Robotics


We explore language-conditioned hierarchical imitation learning for REAL surgery using animal tissues. The framework we develop is broadly applicable to any surgical procedures or general manipulation tasks.

Surgical Robot Transformer: Imitation Learning for Surgical Tasks

Ji Woong Kim, Tony Z. Zhao, Samuel Schmidgall, Anton Deguet, Marin Kobilarov, Chelsea Finn, Axel Krieger

Corl 2024 (oral presentation, 4.5%)


We explore whether surgical manipulation tasks can be learned on the da Vinci system via imitation learning. IL on da Vinci turns out to be non-trivial, due to forward kinematics errors that can reach +/- 5cm. 

Towards Autonomous Eye Surgery Using RGB-D Images


Ji Woong Kim*, Shuwen Wei*, Peiyao Zhang*, Peter Gehlbach, Jin U Kang, Iulian Iordachita, Marin Kobilarov 

RA-L 2024

paper, website


We demonstrate autonomous subretinal injection on pig eyes to deliver drugs below the retinal tissue using RGB-D image feedback.

Autonomous Needle Insertion Inside the Eye for Targeted Drug Delivery

Ji Woong Kim, Peiyao Zhang, Peter Gehlbach, Iulian Iordachita, Marin Kobilarov 

In submission, 2024


We demonstrate for the first time autonomous retinal vein cannulation on pig eyes to deliver drugs into the blood stream. The blood vessel diameter is equivalent to a human hair width, making this task nearly impossible for surgeons but easy for robots.

Autonomous Needle Navigation in Retinal Microsurgery: Evaluation in ex vivo Porcine Eyes

Peiyao Zhang, Ji Woong Kim,  Peter Gehlbach, Iulian Iordachita, Marin Kobilarov 

ICRA 2023

paper


We demonstrate a needle navigation task in eye surgery by combining deep imitation learning and optimal control. This is a follow-up validation work on the CoRL 2020 paper but using animal tissues.

Towards Autonomous Eye Surgery by Combining Deep Imitation Learning and Optimal Control

Ji Woong Kim,  Peiyao Zhang, Peter Gehlbach, Iulian Iordachita, Marin Kobilarov 

CoRL 2020

paper


We solve an autonomous navigation problem in eye surgery using a goal-conditioned imitation learning network trained to imitate expert surgeon trajectories. The surgeon is able to click anywhere on the image and the policy autonomously navigates the surgical tool to the clicked position on the tissue.

Autonomously Navigating a Surgical Tool Inside the Eye by Learning from Demonstration

Ji Woong Kim,  Peiyao Zhang, Peter Gehlbach, Iulian Iordachita, Marin Kobilarov 

ICRA 2020

paper


This is a precursor work to the CoRL 2020 paper, with a slightly different learning formulation and without integrating MPC. This work marked one of the first effort towards autonomous eye surgery.

"OCT-guided Robotic Subretinal Needle Injections: A Deep Learning-Based Registration Approach." IEEE International

Conference on Bioinformatics and Biomedicine (BIBM) 2022