About SPEL
SPEL, led by Prof. Seongmin Heo, develops creative computational methods by utilizing process systems engineering tools that make positive impacts on various industries. Our work spans optimization, simulation, control, and machine learning, applied to electrochemical energy storage, hydrogen and sector-coupled energy systems, membranes and separation processes, and AI-driven process design.
Research Highlights
View all research →Electrochemical Energy Storage
Data-driven and physics-based modeling, diagnosis, and optimization of lithium-ion batteries.
Hydrogen & Sector-Coupled Energy Systems
Superstructure optimization and techno-economic analysis of hydrogen supply chains and energy systems.
Membrane & Separation Processes
Process design and optimization for carbon capture, CO2 conversion, and advanced separations.
Process Systems Synthesis & AI-Driven Design
Superstructure optimization and AI-based surrogate modeling for process synthesis and design.
Graph-Theoretic Design & Control
Graph-theoretic methods for integrated process design and control, including distributed control systems.
Contact
Prof. Seongmin Heo
Department of Chemical & Biomolecular Engineering, KAIST
291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
Email: smheo@kaist.ac.kr · Tel: +82-42-350-3920