معرفی
Dominik Bongartz is a tenure-track assistant professor at KU Leuven's Faculty of Engineering Sciences, Department of Chemical Engineering, where he joined in 2022. He serves as subdivision head of EnergyVille CReaS and is an active member of both the EnergyVille Division and KU Leuven Institute for Energy and Society (KIEM). His academic roles include membership in the Faculty Council of Engineering Sciences, Departmental Council for Chemical Engineering, and as observer of the POC Chemical Engineering Techniques.
Dr. Bongartz's research focuses on developing optimization methods for process design and control in chemical and energy engineering. His work centers on accelerated solution methods for chemical problems and machine learning applications, with particular emphasis on process electrification including heat pumps, electrochemical reactors, and their integration in power-to-x process chains. He is a developer of the open-source optimization software MAiNGO, which has become an important tool in the field.
His recent publications reveal a strong trend toward electrochemical systems optimization, with multiple papers on electrochemical reactors, hydrogen production technologies, and heat pump integration for sustainable energy systems. The research demonstrates sophisticated application of nonconvex optimization techniques to practical engineering problems in the energy transition space.
Professionally, he serves as secretary of the European Committee for the Use of Computers in Chemical Engineering Education (EURECHA) and sits on the editorial board of Computers & Chemical Engineering. These roles highlight his leadership in advancing computational methods in chemical engineering education and research.
Dr. Bongartz teaches multiple courses including Systems Analysis of Chemical Processes, Process Control in the Chemical Industry, Process Simulation in the Chemical Industry at the master's level, and Systems Theory and Control Theory at the bachelor's level. His teaching directly complements his research expertise in process optimization and control.
His research portfolio includes numerous funded projects from 2022-2028, primarily focused on nonconvex optimization methods, electrochemical processes, and power-to-x systems. These projects demonstrate strong industry relevance and alignment with European energy transition goals.
