Ki-Hwan Oh

About

Ki-Hwan Oh is a pioneering researcher at the intersection of robotic surgery, machine learning, and human-robot interaction. His work focuses on advancing minimally invasive surgery through data-driven automation and intuitive control interfaces. Oh’s major contributions include the creation of the Comprehensive Robotic Cholecystectomy Dataset (CRCD), which integrates kinematics, pedal signals, and endoscopic videos—a critical resource for developing AI tools in surgery. He also introduced a framework for automated dissection along tissue boundaries, aiming to enhance precision and reduce surgeon stress during cholecystectomy. His research extends to collaborative manipulation, where he explores how haptic communication can recognize intent in human-robot teams. Additionally, Oh has developed a sensory glove-based user interface for surgical robots, addressing the bulkiness and proprietary limitations of current consoles. With over 19 citations across his most-cited works, his innovative datasets and interfaces are shaping the future of robotic surgery, making procedures safer, more efficient, and more accessible. Oh’s work is particularly notable for its practical focus on real-world surgical challenges, positioning him as a key figure in the next generation of surgical automation.

Research Focus

Key Achievements

Top Papers

1. 1
   Comprehensive Robotic Cholecystectomy Dataset (CRCD): Integrating Kinematics, Pedal Signals, and Endoscopic Videos

   6 citations · 2024
2. 2
   A Framework for Automated Dissection Along Tissue Boundary

   6 citations · 2024
3. 3
   Recognizing Intent in Collaborative Manipulation

   3 citations · 2023
4. 4
   Sensory Glove-Based Surgical Robot User Interface

   2 citations · 2025
5. 5
   Sensory Glove-Based Surgical Robot User Interface

   2 citations · 2024

Key Collaborators

Contact & Links