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Summary: I am a postdoc at Stanford University advised by Chelsea Finn. I am broadly interested in building general-purpose robots that can perform any tasks in the real-world, ranging from surgical to humanoid applications.

Previously, I focused on developing dextrous manipulation policies for the da Vinci robot with Axel Krieger. I also worked on developing autonomous surgical workflows for eye surgery with Marin Kobilarov and Iulian Iordachita. 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: jwbkim@stanford.edu

CV / Google Scholar / LinkedIn / Twitter

News

[2026.5] Giving a talk at Robotics Summit & Expo in Boston, MA

[2026. 4] Giving a talk at UPenn GRASP seminar

[2026. 4] Giving a talk at Global Breast Cancer Conference (GBCC) in Seoul, Korea

[2026. 1] Giving a talk at Samsung Medical Center in Seoul, Korea

[2025. 12] Giving a talk at SNU AI Computing School in Seoul, Korea

[2025. 12] Giving a talk at NeuIPS GenAI4Health in San Diego, CA

[2025. 11] Giving a talk at Clinical Robotic Surgical Association (CRSA) in Los Angeles, CA

[2025. 9] Giving a talk at CoRL at Automating Robotic Surgery Workshop in Seoul, Korea

[2025. 9] Giving a talk at China GI Surgical Forum

[2025. 7] Our Science Robotics paper SRT-H made the July cover and ranked 2nd in Altmetric score among all SR papers. More than 280 new articles has been written about the work!

[2025. 4] Giving a talk at Korean Society of Endo-Laparoscopic & Robotic Surgery (KSERS) in Seoul, Korea

[2024. 12] Our Surgical Robot Transformer (SRT) paper has been covered in the Washington Post, among many other news outlets!

[2024. 11] Giving an oral presentation at Conference on Robot Learning on Surgical Robot Transformer (SRT) in Munich, Germany

Selected Publications

VLA Fine-Tuning for Ego-Centric Human and Robot Data

Under Review

We explore how human data can teach robots perform new tasks that did not appear in the robot dataset.

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

Science Robotics (Cover of July 2025)

2nd highest Altmetric score among all Science Robotics papers

website

We explore language-conditioned hierarchical imitation learning for real surgery using animal tissues.

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%)

website

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.

Journal Papers

[J.9] J. W. Kim, J. T. Chen, P. Hansen, L. X. Shi, A. Goldenberg, S. Schmidgall, et al. SRT-H: A hierarchical framework for autonomous surgery via language-conditioned imitation learning. Science Robotics (2025), 10(104).
[J.8] S. Schmidgall, J. D. Opfermann, J. W. Kim, A. Krieger. Will your next surgeon be a robot? Autonomy and AI in robotic surgery. Science Robotics (2025), 10(104).
[J.7] M. Esfandiari, J. W. Kim, P. Zhang, J. S. Heng, P. Gehlbach, R. H. Taylor, I. Iordachita. Bimanual Robotic Eye Manipulation Using Adaptive Sclera Force Control: Towards Safe Retinal Vein Cannulation. IEEE Transactions on Medical Robotics and Bionics (2025).
[J.6] S. Schmidgall, J. W. Kim, A. Kuntz, A. E. Ghazi, A. Krieger. General-purpose foundation models for increased autonomy in robot-assisted surgery. Nature Machine Intelligence (2024), 6, 1275-1283.
[J.5] S. Schmidgall, C. Harris, I. Essien, ... J. W. Kim, et al. Evaluation and mitigation of cognitive biases in medical language models. npj Digital Medicine (2024), 7(1), 295.
[J.4] S. Schmidgall, J. W. Kim, A. Krieger. Robots learning to imitate surgeons—challenges and possibilities. Nature Reviews Urology (2024), 21(8).
[J.3] P. Zhang, J. W. Kim, P. Gehlbach, I. Iordachita, M. Kobilarov. Autonomous needle navigation in subretinal injections via iOCT. IEEE Robotics and Automation Letters (RA-L) (2024), 9(5).
[J.2] J. W. Kim, S. Wei, P. Zhang, P. Gehlbach, J. U. Kang, I. Iordachita, M. Kobilarov. Towards autonomous retinal microsurgery using RGB-D Images. IEEE Robotics and Automation Letters (RA-L) (2024), 9(4).
[J.1] M. G. Urias, N. Patel, C. He, A. Ebrahimi, J. W. Kim, I. Iordachita, P. L. Gehlbach. Artificial intelligence, robotics and eye surgery: are we overfitted? International Journal of Retina and Vitreous (2019), 5(1).

Conference Papers

[C.13] J. W. Kim, K. Wang, S. Liu, Z. Fu, C. Gao, J. Lai, C. Finn. Ego-Pi: VLA Fine-Tuning for Ego-Centric Human and Robot Data. Under review (2025).
[C.12] L. Zbinden, N. Nelson, J. T. Chen, X. Chen, J. W. Kim, M. Azizian, A. Krieger, S. Huver. Cosmos-Surg-dVRK: World Foundation Model-based Automated Online Evaluation of Surgical Robot Policy Learning. Under review (2025).
[C.11] N. Barnes, J. W. Kim, L. Di, H. Qu, A. Bhattacharjee, et al. Autonomous Soft Robotic Guidewire Navigation via Imitation Learning. Under review (2025).
[C.10] J. Haworth, J. T. Chen, N. Nelson, J. W. Kim, M. Moghani, C. Finn, A. Krieger. SutureBot: A Precision Framework & Benchmark For Autonomous End-to-End Suturing. NeurIPS (2025).
[C.9] J. T. Chen, X. Chen, J. W. Kim, P. M. Scheikl, R. J. Cha, A. Krieger. SurgiPose: Estimating Surgical Tool Kinematics from Monocular Video for Surgical Robot Learning. IROS (2025).
[C.8] J. W. Kim, T. Z. Zhao, S. Schmidgall, A. Deguet, M. Kobilarov, C. Finn, A. Krieger. Surgical Robot Transformer (SRT): Imitation Learning for Surgical Tasks. Conference on Robot Learning (CoRL) (2024).
[C.7] M. Esfandiari, J. W. Kim, B. Zhao, G. Amirkhani, M. Hadi, P. Gehlbach, I. Iordachita. Cooperative vs. teleoperation control of the steady hand eye robot with adaptive sclera force control: A comparative study. IEEE International Conference on Robotics and Automation (ICRA) (2024).
[C.6] P. Zhang, J. W. Kim, P. Gehlbach, I. Iordachita, M. Kobilarov. Autonomous needle navigation in retinal microsurgery: Evaluation in ex vivo porcine eyes. IEEE International Conference on Robotics and Automation (ICRA) (2023).
[C.5] K. Mach, S. Wei, J. W. Kim, A. Martin-Gomez, P. Zhang, J. U. Kang, et al. OCT-guided robotic subretinal needle injections: A deep learning-based registration approach. IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2022).
[C.4] S. Wei, J. W. Kim, A. Martin-Gomez, P. Zhang, I. Iordachita, J. U. Kang. Region targeted robotic needle guidance using a camera-integrated optical coherence tomography. Optical Coherence Tomography (2022).
[C.3] P. Zhang, J. W. Kim, M. Kobilarov. Towards safer retinal surgery through chance constraint optimization and real-time geometry estimation. IEEE Conference on Decision and Control (CDC) (2021).
[C.2] J. W. Kim, P. Zhang, P. Gehlbach, I. Iordachita, M. Kobilarov. Towards autonomous eye surgery by combining deep imitation learning with optimal control. Conference on Robot Learning (CoRL) (2021).
[C.1] J. W. Kim, C. He, M. Urias, P. Gehlbach, G. D. Hager, I. Iordachita, M. Kobilarov. Autonomously navigating a surgical tool inside the eye by learning from demonstration. IEEE International Conference on Robotics and Automation (ICRA) (2020).

Technical Reports

[T.3] S. Schmidgall, J. W. Kim, J. Jopling, A. Krieger. (2024). General surgery vision transformer: A video pre-trained foundation model for general surgery. arXiv preprint arXiv:2403.05949.
[T.2] H. Ding, Y. Zhang, H. Shu, X. Lian, J. W. Kim, A. Krieger, M. Unberath. (2024). Towards robust algorithms for surgical phase recognition via digital twin-based scene representation. arXiv preprint arXiv:2410.20026.
[T.1] J. W. Kim, P. Zhang, P. Gehlbach, I. Iordachita, M. Kobilarov. Micromanipulation in Surgery: Autonomous Needle Insertion Inside the Eye for Targeted Drug Delivery. Robotics: Science and Systems (RSS) Workshop (2023).

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