PhD candidate at Seoul National University (CCEL, Prof. Jeong Woo Han) and Presidential Science Scholar. I study catalysis and energy phenomena and build AI-driven simulation — machine-learning interatomic potentials, knowledge distillation, and generative models — to bridge the long-standing gap between theory and experiment.
- Why — conventional simulation (DFT, MD) leaves a wide gap with experiment; AI can close it
- What — electrocatalysis (OER · HER · CER), single-atom catalysis, energy-conversion materials
- How — MLIP development & distillation, generative models, ML-accelerated DFT/MD, high-throughput screening
- CatBench — MLIP benchmarking framework · Cell Reports Physical Science · live leaderboard
- MLIP-driven interpretation of experiments — Ru-cluster HER (Energy & Environmental Science), reversible solid-oxide cells (Nature Energy)
Including these, 6 first-author and 5 co-author papers. Full list → Google Scholar · jinukmoon.github.io/publications
Website · CV · Google Scholar · LinkedIn · jumoon@snu.ac.kr
Off-screen: tennis, squash, and coffee chats — always open to research collaborations.
