Jung Min LEE (이정민)

M.S. Student, Dept. of Electrical and Computer Engineering
Seoul National University
Jung Min LEE
🚨 I'm looking for research intern opportunities in embodied AI or robotics. Feel free to reach out!

About

Hi! I'm Jung Min from 🇰🇷. I'm a second-year M.S. student at Cognitive Machine Learning Laboratory, advised by Prof. Jung Woo Lee, in the Department of Electrical and Computer Engineering at Seoul National University (SNU). I received my B.S. in Physics from SNU.

Research Keywords

Robot Learning Reinforcement Learning Embodied AI
How to solve real-world problems with generalized intelligence

AI has demonstrated strong performance over the past five years, yet it remains an open question whether AI can reliably solve real-world problems. To address this gap, I believe the most important capability AI must achieve is generalized intelligence.

With this goal in mind, I am currently focusing on data scaling for real-world agents. Data scaling is one of the most effective paths toward generalized intelligence, but it remains challenging in real-world settings. My work aims to develop new methods to scale real-world agent data and, ultimately, enable foundation-model-level generalized intelligence.

News

Apr 2026 “MVP-LAM: Learning Action-Centric Latent Action via Cross-Viewpoint Reconstruction” is accepted to ICML 2026!
Feb 2026 Released “MVP-LAM: Learning Action-Centric Latent Action via Cross-Viewpoint Reconstruction” on arXiv.

Education

2025 — Present
M.S., Cognitive Machine Learning Laboratory, Dept. ECE, Seoul National University
Advisor: Prof. Jung Woo Lee  ·  Robot Learning & Reinforcement Learning
2021 — 2025
B.S., Physics and Astronomy & Artificial Intelligence, Seoul National University
Cum Laude
2018 — 2021
Chung-Nam Samsung Academy

Publications

International Conference

  1. MVP-LAM thumbnail
    MVP-LAM: Learning Action-Centric Latent Action via Cross-Viewpoint Reconstruction
    Jung Min Lee, Dohyeok Lee, Seokhun Ju, Taehyun Cho, Jin Woo Koo, Li Zhao, Sangwoo Hong, Jungwoo Lee
    ICML 2026
  2. Viewpoint-Invariant Latent Action Learning from Human Video Demonstrations
    Jung Min Lee, Dohyeok Lee, Jungwoo Lee
    NeurIPS SpaVLE Workshop, 2025
  3. Dynamics-Aligned Flow Matching Policy for Robot Learning
    Dohyeok Lee, Jung Min Lee, Munkyung Kim, Seokhun Ju, Seungyub Han, Jin Woo Koo, Jungwoo Lee
    CVPR EAI Workshop, 2025
  4. View-Imagination: Enhancing Visuomotor Control with Adaptive View Synthesis
    Dohyeok Lee, Munkyung Kim, Jung Min Lee, Seungyub Han, Jungwoo Lee
    CVPR EAI Workshop, 2025

Preprint

  1. Dynamics-Alignment thumbnail
    Learning Generalizable Visuomotor Policy through Dynamics-Alignment
    Dohyeok Lee, Jung Min Lee, Munkyung Kim, Seokhun Ju, Jin Woo Koo, Kyungjae Lee, Dohyeong Kim, TaeHyun Cho, Jungwoo Lee
    arXiv preprint, 2025

Open Source

IsaacSim-Franka  ⭐ 18

Teaching

Skills

Python
100
PyTorch
100
NumPy
95
MATLAB
90
C++
90
NVIDIA IsaacSim
90
MuJoCo
85
TensorFlow
60
ROS / R
60
MoveIt2
60
JAX
50