Atomistic Intelligence Lab

지능형화공재료연구실

AI infrastructure and agents for materials discovery.
From atomistic models to catalysis and energy materials.

Core Philosophy

Atomistic Intelligence Lab is building toward an Agent-Driving Lab (ADL)—our term for a research environment where AI agents connect hypothesis generation, simulation, analysis, and experimental feedback. We collaborate across chemical-engineering applications while developing an independent methodological core in MLIP infrastructure, scientific agents, and research automation. Agents expand the space we can explore; researchers remain responsible for choosing meaningful questions and validating the answers.

Experiment as Ground Truth

"No matter how beautiful the theory is."

- R. Feynman (1964)
Adopt AI Responsibly

Take responsibility for the quality of AI-generated outcomes.

Research Directions

Agent-Driving Lab

Scientific agents coordinate candidate generation, simulation, analysis, and experimental feedback. We develop practical closed loops that enlarge the searchable design space without overstating full autonomy.

ICLR 2026 AI4Mat
Chem. Eng. J. (2024)
ACS Energy Lett. (2025)

AI Infrastructure

We make atomistic foundation models lighter, faster, easier to adapt, and more consistently evaluated. Distillation, efficient finetuning, benchmarking, and standardized agent interfaces form the methodological core of the lab.

AI4Mat-NeurIPS (2025)
Cell Rep. Phys. Sci. (2025)
Nat. Sensors (2026)

Collaborative Applications

We pursue independent scientific questions with experimental collaborators across catalysis and energy materials—from thermochemical and electrochemical conversion to emerging homogeneous systems.

Heterogeneous & homogeneous catalysis
Energy materials · AI4Chem
Academic Communities

We will build sustained relationships across three communities: KIChE and KSIEC as our core chemical-engineering societies; KIM for the computational materials community; and ICML, ICLR, and NeurIPS for the international AI community. The aim is to connect application-driven chemical engineering with rigorous atomistic modeling and frontier AI methodology.

What We Offer
Atomistic Intelligence Lab starter pack - Mac mini, MacBook, DJI mic, Claude Max, gym membership
For Your Research
  • Claude Max for every lab member
  • GPU clusters (A6000/L40S, H100 via KISTI)
  • VASP, LAMMPS, PyTorch, ASE, custom tools
  • Direct experimental collaborator connections
For Your Life
  • Gym membership (we pay for it)
  • Flexible working hours (output > hours)
  • Unlimited deep discussions with Dr. Choung
  • 1-on-1 mentoring for YOUR career goals
  • Asking "why?" is encouraged, not punished
FAQ
Do I need prior DFT or ML experience?
No. We'll teach you everything. We care about curiosity and drive, not a perfect GPA or prior experience.
I only have experimental experience. Can I apply?
Yes, and we actually welcome it. Computational researchers who understand experiments run the best simulations. We'll teach the coding.
Is the lab English-friendly?
Yes. All group meetings and internal communication can be in English. Papers are in English. International students are welcome.
Do you really provide Claude Max?
Yes. AI tools are research infrastructure. We invest, not economize.
How many hours per week?
We don't count hours. Ask good questions, make steady progress, and take care of your health. That's it.
What's the lab culture like?
We value: intellectual honesty, curiosity, kindness, and taking care of yourself. We don't value: performative busyness, hierarchy for its own sake, or suffering as a badge of honor.
How are research topics decided?
Initially the advisor suggests directions, then you gradually take the lead. The ultimate goal is for you to find your own compelling questions.
Career paths after graduation?
Academia, national labs, industry R&D, AI/ML engineering, and more. The combination of atomistic simulation + AI skills is in demand everywhere.
How much coding skill do I need?
Basic Python is enough. You'll learn the rest on the job. AI tools have lowered the barrier significantly.

Interested?

Graduate students, postdocs, and undergrads all welcome. No simulation experience required.

No formal deadline. Positions open until filled.