Seong Hyeon Park
Seong Hyeon Park is a researcher specializing in efficient algorithms for robot learning and high-dimensional computer vision, including dexterous robotic hand policies, 3D/4D reconstruction, and video motion estimation. He earned his Ph.D. at KAIST under the supervision of Dr. Jinwoo Shin and is currently a Visiting Scholar at the Global AI Frontier Lab at New York University. He is a co-author of Pose6DAug, a physically plausible multi-view object swapping framework for robot data augmentation, and is actively on the job market.
“The core achievement of this paper is a framework that recycles a robot's past successful actions to teach it how to handle new objects it has never seen before.”
Source→“By fine-tuning Vision-Language-Action (VLA) policies on this augmented data, they achieved a 16.5% relative to the state-of-the-art baseline on novel objects.”
Source→AI-extracted from podcast / newsletter / paper summaries. May contain errors.