| CARVIEW |
Hello, I'm Juhan Park
I am a Ph.D student at Korea Unversity, where I work with Sungjoon Choi on artificial inteligence and robotics. Previously, I received my M.S. from the Department of Artificial Intelligence at Chung-Ang University, advised by Kyungjae Lee.
My focus is on robot learning for autonomous systems, with a recent emphasis on dexterous hand manipulation. I aspire to integrate this robotic intelligence into the agricultural sector to enable sophisticated automation.
News
- [October 2025]: Our lab is conducting a joint demonstration with RLWRLD. (video link)
- [March 2025]: Started my Ph.D. at Korea University, advised by Sungjoon Choi.
- [February 2025]: Graduated from the Department of Artificial Intelligence at Chung-Ang University with a M.S. degree..
- [Feburary 2025]: I am presenting our work about placement aware grasp planning in Korea Robotics Society Annual Conference (KRoC) as invited speaker in flagship conference session.
- [October 2024]: Our paper about Placement Aware Grasp Planning for Efficient Sequential Manipulation got published to ECAI 2024.
- [May 2023]: Our paper about Efficient Task Planning with MCTS got published to ICRA 2023.
- [March 2023]: I have started my M.S. at the Department of Artificial Intelligence at Chung-Ang University, advised by Kyungjae Lee.
Publications
Learning Feasibility from Failure Data in Vision–Language–Action Models
We propose VINE, a dual-system framework that injects failure-aware reasoning into VLAs. System 1 executes grounded action chunks, while System 2 builds a tree of thought states and scores candidate subgoals using both success and failure data.
Foundation Model-Driven Framework for Human-Object Interaction Prediction with Segmentation Mask Integration
This work utilizes a segmentation foundation model to perform the Human-Object Interaction (HOI) detection task.
Placement Aware Grasp Planning for Efficient Sequential Manipulation
Efficient task planning with MCTS considering placement constraints.
Perturbation-Based Best Arm Identification for Efficient Task Planning with Monte-Carlo Tree Search
Perturbation-based best arm identification for efficient task planning with Monte-Carlo Tree Search.