معرفی
Prof. Dr. Martin Frank is a Professor and Department Head at Karlsruhe Institute of Technology (KIT), leading the Computational Science and Mathematical Methods (CSMM) research group within the Scientific Computing and Mathematics department at the Scientific Computing Center (SCC). He maintains dual affiliation with both the SCC and the Institute for Applied and Numerical Mathematics in the Department of Mathematics at KIT.
His research focuses on interdisciplinary mathematical modeling with applications across various scientific domains. The CSMM group under his leadership develops and applies modern mathematical techniques including modeling, simulation, optimization, inverse problems, uncertainty quantification, and machine learning to practical challenges. His work particularly emphasizes kinetic theory, with applications in fluid dynamics, radiation simulation, and medical physics.
Prof. Frank teaches courses including Uncertainty Quantification, Introduction to Kinetic Theory, and seminars on Computational Science and Mathematical Methods across multiple semesters from Winter 2018/19 through Summer Semester 2025. He has established educational initiatives like CAMMP (Computational Applied Mathematics in Multidisciplinary Projects) that bring real-world mathematical modeling into school classrooms.
Throughout his career, Prof. Frank has mentored numerous doctoral students whose work spans mathematical modeling, machine learning applications, kinetic equations, and uncertainty quantification. His former students have pursued academic careers at institutions like TU Dresden, TU Eindhoven, and Oak Ridge National Laboratory, as well as industry positions.
The CSMM research group maintains active collaborations with various institutions including the German Cancer Research Center (DKFZ) through HIDSS4Health, and participates in major research initiatives like the Sonderforschungsbereich 1173 (Collaborative Research Center). The group also contributes to open-source software development, particularly in lattice Boltzmann methods through the OpenLB project.
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