· 약력
2023.03 ~ 현재 중앙대학교 물리학과 조교수
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
Research area: Nuclear fusion simulation (핵융합 플라즈마, 인공지능 응용)

Nuclear fusion is a process where atomic nuclei combine to form a heavier nucleus, releasing a tremendous amount of energy in the process. This is the same process that powers stars, including our own Sun. Scientists have been trying to harness the power of nuclear fusion to create a new, clean source of energy for decades.

A promising way to achieving nuclear fusion on Earth is through the use of a device called a tokamak (eg. KSTAR in Korea). A tokamak is a device that uses a magnetic field to confine a plasma in the shape of a torus (a donut shape). The tokamak is designed to heat the plasma to extremely high temperatures and densities, allowing the atomic nuclei to fuse together.

Recently, with the advancements in AI and GPU computing technologies, new methods for simulating tokamak plasma in different ways are being developed. Our lab uses AI and simulation to virtually experiment with plasma and research tokamak optimization for effective nuclear fusion.


1. Fusion plasma theory & experiments (핵융합 및 플라즈마 이론)
- Energetic particle, Alfvén eigenmode
- KSTAR (KR), VEST (KR), DIII-D (US), ITER (international)

2. AI for physics (인공지능 물리응용)
- Deep learning, Reinforcement learning, Generative AI
- Physics-informed neural network (PINN)

3. Simulation & optimization (핵융합 시뮬레이션 및 최적화)
- Plasma control/optimization
- Tokamak simulation