
Marcin Sosnowski
دانشیار · Numerical Modelling
Max Planck Institute for Mathematics in the Sciencesمعرفی
Associate Professor Marcin Sosnowski is affiliated with the Faculty of Science and Technology at Jan Dlugosz University in Czestochowa. He has held leadership roles including Institute Director, Vice Dean, and Dean of the Faculty. His career spans academia and industry, with prior experience at General Electric's Engineering Design Center.
His educational background includes:
- Graduated from the Faculty of Electrical Engineering at Czestochowa University of Technology in 2001.
- PhD in Mechanical Engineering (year not specified).
Professor Sosnowski's research focuses on numerical modeling and simulation of thermal and fluid processes. Key areas include combustion, heat and mass transfer, adsorption, and heat pumps. He specializes in computational methods, particularly Computational Fluid Dynamics (CFD) and domain discretization techniques for complex systems such as combustion chambers and fluidized reactors.
His recent publications (2024-2025) demonstrate a strong trend in applying advanced computational techniques to energy systems. This includes work on CO2 capture via chemical looping combustion, AI-driven modeling for complex systems, and coupled CFD-DEM simulations for fluidized sorption reactors. His research bridges theoretical innovation with practical engineering applications in clean energy and thermal systems.
He has actively contributed to the academic community through:
- Reviewing over 150 scientific papers.
- Serving on scientific and organizing committees for more than 30 conferences.
- Holding editorial roles (topic editor, guest editor, editorial board member) for over 20 journals.
As a project leader, he has managed and coordinated multiple externally funded research initiatives. His leadership extends to academic administration, having served as Dean of the Faculty of Science and Technology. While specific lab affiliations aren't detailed, his work involves advanced computational modeling that likely utilizes high-performance computing resources.
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