· 약력
2023.03 ~ 현재 중앙대학교 물리학과 부교수
2022.08 ~ 2023.02 미국 Princeton University 박사후 연구원
2019.01 ~ 2019.08 영국 EUROfusion (CCFE) 방문연구원
2017.03 ~ 2022.08 서울대학교 공학박사 (핵융합 플라즈마)
2012.03 ~ 2017.02 서울대학교 공학사 (핵공학)

· 연구분야
Nuclear fusion, the energy source of the Sun, is a clean and sustainable future energy solution capable of addressing the rapidly growing energy demand of the AI era. Our lab solves key problems in nuclear fusion research using AI and simulations, while also developing advanced AI methodologies inspired by fundamental physical principles.

1. Nuclear fusion & plasma (핵융합 플라즈마)
- Fusion plasma simulation (핵융합 플라즈마 시뮬레이션)
- Tokamak control (토카막 제어)
- Nuclear fusion experiments (핵융합 실험)

2. Physics+AI (인공지능 물리학)
- Quantum machine learning (양자머신러닝)
- Physics-informed machine learning (물리정보신경망)
- AI application for physics (인공지능 물리응용)

Representative papers:
[1] J. Seo et al., Avoiding fusion plasma tearing instability with deep reinforcement learning, Nature 626 (2024) 746. (과기부 우수성과 100선)
[2] Y.-S. Na*, J. Seo* et al., Observation of a new type of self-generated current in magnetized plasmas, Nat. Commun. 13 (2022) 6477.
[3] J. Seo et al., Feedforward beta control in the KSTAR tokamak by deep reinforcement learning, Nucl. Fusion 61 (2021) 106010.
[4] J. Seo, Solving real-world optimization tasks using physics-informed neural computing, Sci. Rep. 14 (2024) 202. (TOP 100 논문 선정)