Machine Learning & Intelligent Control Lab.
AI Graduate School (AIGS) & Department of Electrical Engineering (EE)
Ulsan National Institute of Science and Technology (UNIST)
50 Unist-gil, Ulsan, 44919, South Korea
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.
The research of our group focuses on the development of breakthrough machine learning (ML) algorithms, theoretical 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
Research Summary: Exploration and Exploitation Methods for Reinforcement Learning
- We are currently looking for highly motivated interns, M.S. & Ph.D. students in machine learning fields !
(If you are interested, email me your CV and transcript.)
[2022/07/15] Lecture: UNIST AI Innovation Park, “4th AI Novatus Academia,” Week 3.
[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.