I am an MS/Ph.D student majoring in Artificial Intelligence at Yonsei University, advised by Prof. Youngwoon Lee.
My research focuses on the intersection of Robotics and AI. I am particularly interested in building intelligent agents that can reason and make decisions in the real world by leveraging Foundation Models and Reinforcement Learning.
Previously: Research intern at Microsoft Research Asia (MSRA), MLCS Lab (Prof. Jongeun Choi), and CLVR Lab (Prof. Joseph J. Lim).
Hokyun Im • Euijin Jeong • Andrey Kolobov • Jianlong Fu • Youngwoon Lee
We introduce TwinVLA, a vision-language-action (VLA) model for bimanual manipulation that fuses pretrained single-arm VLA models. This design reduces reliance on scarce bimanual data while achieving comparable performance.
Project Lead, Yonsei Drone (2024)
Previously, distance-sensing sensors such as depth cameras were necessary for drone navigation. With the advancement of foundation models, we successfully accomplished indoor navigation using only a front-facing RGB image by leveraging the CrossFormer model.
Yonsei Drone (2023)
Fully autonomous outdoor drone navigation using GPS to travel long distances, avoid obstacles, reach the destination to deliver items, and return safely.
I led the development of building approach algorithms, and worked on safe landing using Sim2Real RL.
dm_control based bimanual tabletop simulation / dataset for testing bimanual robot policy.
A student-led drone research society. I served as the 4th president.
The leading academic society for AI at Yonsei University. I was a 11th member.
A toy project that allows interactive, real-time manipulation of the latent representation of a VAE on a webpage. Implemented using TensorFlow.js.
HTML games developed in JavaScript during spare time in the military. Quite fun to play haha.
A simple pendulum simulator designed as an educational tool. It allows students to explore and understand the principles of PID control.