Physical AI for Transfomative Materials Discovery
Career History
- 1986 : B.S. Chemistry, Seoul National University
- 1989 : M.S. Chemistry, Seoul National University
- 1998 : Ph.D. Inorganic Chemistry, University of Michigan
- 1998-2002: Post-Doc, Iowa State University and Ames Laboratory
- 2002-2004: Post-Doc, Lawrence Livermore National Laboratory
- 2004-2012: Assistant Professor, University of Nebraska-Lincoln
- 2012-2020: Associate Professor, UNIST
- 2021-2023: Director, National Chemical Research Information Center (Ministry of Science and ICT)
- 2022: Chair, Inorganic Chemistry Division, Korean Chemical Society
- 2022-2023: Chair, Ulsan Section, Korean Chemical Society
- 2020-Present: Professor, UNIST
Intro
A central task of our research is to embed algorithms directly into the discovery process. We build closed-loop workflows that connect experimental data to decision-making, enabling the next round of design to be guided by quantitative learning rather than human intuition alone. By transforming trial-and-error into an adaptive and reproducible discovery engine, we aim to accelerate how new materials are conceived, validated, and refined from fundamental design principles to measurable function. In doing so, we seek to bridge imagination and implementation—bringing dream materials to real-world function.
Research Field
Reticular Chemistry, Algorithm, Metal–Organic Frameworks (MOFs), Autonomous Experimentation