Machine Learning & Intelligent Control Lab.

Principal Investigator


Seungyul Han

Assistant Professor

AI Graduate School (AIGS) & Department of Electrical Engineering (EE)

Ulsan National Institute of Science and Technology (UNIST)

50 Unist-gil, Ulsan, 44919, South Korea

[Google Scholar]   [Curriculum Vitae]


  • Tel         +82-52-217-3455
  • Office    Room. 301-1, Building 106, UNIST


Seungyul Han is an assistant professor in the Artificial Intelligence Graduate School (AIGS) and in the department of Electrical Engineering (EE) at the Ulsan National Institute of Science and Technology (UNIST). He received B.S. (Double major in Mathematical Science) and M.S. degrees in Electrical Engineering from Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea in 2013 and 2016, respectively. He also received his Ph.D. degree in Electrical Engineering from KAIST. Prior to joining UNIST, he was an postdoctoral researcher at Institute of Information Electronics in KAIST, and he is now an assistant professor in UNIST. His main research interests include reinforcement learning, machine learning, deep learning, multi-agent systems, signal processing, and intelligent control systems.​​​

Research Areas

The research of our group focuses on the development of breakthrough machine learning (ML) algorithmstheoretical improvements based on mathematics, and real-world ML applications for industrial automation. In order to conduct influential research in the core areas of artificial intelligence (AI), we mainly consider the following research topics:

  • Reinforcement Learning
  • Robust/Safe Learning
  • Domain Adaptation/Imitation Learning
  • Multi-Agent Systems
  • Statistical Learning
  • Intelligent Control systems
  • Signal Processing

1Research Summary: Exploration and Exploitation Methods for Reinforcement Learning

- We are currently looking for highly motivated interns, M.S., Ph.D., and Combined M.S./Ph.D. students in machine learning fields !

(If you are interested, email me your CV and transcript.)


[2023/09/22] Paper “Domain Adaptive Imitation Learning with Visual Observation” is accepted to NeurIPS 2023.

[2023/09/15] Lectures: UNIST AI Innovation Park, “6th AI Novatus Academia, 3/4th AI Novatus Academia 경남.”

[2023/03/01] Sunwoo Lee, Sanghyeon Lee, and Taehyun Ahn joined our lab !

[2023/01/27] Lectures: UNIST AI Innovation Park, “4/5th AI Novatus Academia, 2nd AI Novatus Academia 경남.”

[2022/07/25] Lecture: LG DXI course, “Reinforcement Learning.”

[2022/07/01] Jeongmo Kim, Minung Kim, and Heeseong Eom (intern) joined our lab !

[2022/05/25] Lecture: 한국통신학회(KISC) AI Frontiers Summit (AIFS) Tutorial, “강화학습 및 응용에 대한 최신 연구 동향”

[2022/05/15] Paper “Robust imitation learning against variations in environment dynamics” is accepted to ICML 2022.

[2022/04/01] Project PI: 자율 드론 실용화를 위한 목적지향 강화학습 핵심기술 개발 (IITP 사람중심인공지능 핵심원천기술개발, 22.04 – 26.12)

[2022/03/18] Lecture: UNIST AI Innovation Park, “1st AI Novatus Academia 경남,” Week 3.

[2022/03/01] Yonghyeon Jo and Junghyuk Yum joined our lab !

[2022/01/28] Lecture: UNIST AI Innovation Park, “3rd AI Novatus Academia,” Week 3 & 4.

[2022/01/24] Lecture: 한국통신학회(KICS) 단기강좌 (머신러닝/강화학습의 기초 및 응용 강좌),  “강화학습의 기초.”

[2021/11/01] I have joined the Artificial Intelligence Graduate School and the Department of Electrical Engineering at Ulsan National Institute of Science and Technology (UNIST) as an assistant professor.

[2021/09/29] Paper “A max-min entropy framework for reinforcement learning” is accepted to NeurIPS 2021.

[2021/05/08] Paper “Diversity actor-critic: Sample-aware entropy regularization for sample-efficient exploration” is accepted to ICML 2021.