Process Engineering & Automation Lab

공정 공학 및 자동화 연구실

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At the "Process Engineering & Automation Lab (PEAL)", we merge artificial intelligence with chemical manufacturing to pioneer eco-friendly, automated processes. Our research area includes both hardware like robotic automation and image sensors and software advancements in simulation, data processing, and algorithms for machine learning, optimization, and control. Our goal is to lead the industry towards carbon neutrality by 2050 through smart, sustainable and automated process. If you're passionate about AI and automation in pursuit of a greener future, we welcome your contact.

Major research field

Process System, Automation, Artificial Intelligence, Fluid Analysis

Desired field of research

CCUS, Gas Hydrate

Research Keywords and Topics

Process System, Automation, Artificial Intelligence, CCUS, Gas Hydrate

Research Publications

· Automatica, “Probability Density Function-based Stochastic Nonlinear Model Predictive Control using Fokker-Planck Equation,” T. H. Oh, J. W. Kim, Y. Kim, and J. M. Lee, 2024 (Under Review).
· AIChE Journal, “Integration of Reinforcement Learning and Model Predictive Control to Optimize Semi-batch Bioreactor,” T. H. Oh, H. M. Park, J. W. Kim, and J. M. Lee, 2022.
· Computers & Chemical Engineering, “Quantitative comparison of reinforcement learning and data-driven model predictive control for chemical and biological processes,”, T. H. Oh 2024.


  • EC. 화공
  • EC01. 화학공정
  • EC0103. 공정시스템기술


  • 정보-지식-지능화 사회 구현
  • 012300. 인공지능/지능로봇 기술


  • 고효율화기술
  • 친환경 제조공정 및 소재효율성 향상
  • 351. Green Process 기술


  • ET 분야
  • 청정생산
  • 050311. 청정원천공정 기술