Hi, I'm Inseok.

I'm a graduate researcher who works on process systems end-to-end — from hardware on a bench to simulation, optimization, and the AI tooling that ties it together. I'm pursuing an MSc in Chemical & Biological Engineering at Korea University, with my research carried out at the Korea Institute of Science and Technology (KIST).

My starting point was an integrated hydrogen energy system that I helped design, build, and operate — reactor, balance-of-plant, fuel-cell integration, and the thermal management that keeps it all alive. That project taught me what simulation alone can't: how a system behaves when real thermal limits, purity tolerances, and scale-up constraints push back. On the computational side, I build physics-based thermal solvers and Aspen Plus process models, and drive them with multi-objective optimization — NSGA-II with machine-learning surrogates. And I develop the AI-assisted engineering tooling that makes all of this faster: automation pipelines and multi-agent orchestration.

My current work extends into atomic layer deposition (ALD) on two tracks: synthesizing catalysts with atomic-scale precision, and quantifying the life-cycle footprint of ALD processes — precursor consumption, energy intensity, and emissions. It's the same engineering discipline, applied at the opposite end of the length scale.