Having accepted the offer of the Heisenberg Professorship (W3) in “Data Analytics in Engineering” at the University of Stuttgart, Dr.-Ing. Felix Fritzen took up the position on January 7.
Fritzen studied mechanical engineering from 2001 to 2006 and technomathematics from 2004 to 2007, both at the University of Karlsruhe. In 2007, he was awarded the Karl Benz Prize for his “Diplom” thesis on the mechanical engineering program in recognition of it being one of the two best theoretical “Diplom” theses.
In 2011, Fritzen gained a doctorate from the Karlsruhe Institute of Technology (KIT) on the basis of his doctoral thesis on “Microstructural modeling and computational homogenization of the physically linear and nonlinear constructive behavior of micro-heterogeneous materials”. The thesis also won him the KIT Doctoral Award in the field of matter and materials in 2012. He worked as a postdoc at KIT from 2011 to 2012 and headed up KIT’s Young Investigator Group on “Computer-Aided Material Modeling” from 2012 to 2015, which looked at microstructure modeling, numerical homogenization and efficient multiscale simulations. Finally, in 2015 he moved to the University of Stuttgart and was the leader of the DFG-funded Emmy Noether Group on “EMMA – Efficient Methods for Mechanical Analysis” (DFG FR2702/6) until he accepted the Heisenberg Professorship.
Fritzen has also been an associate member of the SimTech Cluster of Excellence since 2015. In Project Network 1, he worked with Oliver Kunc on the “Data-assisted Constitutive Models” project in the now defunct EXC 310 Cluster of Excellence. In the new EXC 2075 Cluster of Excellence, he is a participating researcher in project networks 3 (“Data-integrated model reduction for particles and continua”) and 5 (“On-the-fly Model Modification, Error Control, and Simulation Adaptivity”). He also manages the PN3-1 project, entitled “Processing uncertain microstructural data”, which is being conducted in close cooperation with the PN 5-4 tandem project of the same name, in turn managed by Prof. Dr. Andrea Barth. The main focus of the project is image-based prediction of micromechanical properties for stochastic microstructures.
Ultimately, SimTech and the excellent mechanical science environment were key to Felix Fritzen’s decision to move to Stuttgart. “Since my arrival here,” he explains, “the vigorous culture of knowledge-sharing with and within SimTech has had a significant influence on me and my work. In my scientific activities, this has mostly been visible in the areas of reduced-order modeling, material modeling, uncertainty quantification and data-based modeling. I immediately felt at home here – both in personal and research terms. My colleagues and students have been and still are a big part of that.”
The DFG Heisenberg Professorship (W3) in “Data Analytics in Engineering” (DFG-FR 2702/8) at the University of Stuttgart marks the beginning of a new phase in Fritzen’s career. The aim of the professorship is to develop data-driven simulation techniques and thus to strengthen and establish simulation science as a discipline. The professorship is based in the Stuttgart Center for Simulation Science (SC SimTech) and Faculty 2 and integrated into the “Data-Integrated Simulation Science” Cluster of Excellence (EXC 2075).
“I’m thrilled to be adding to the expertise of the University of Stuttgart and the SimTech Cluster of Excellence with my research in the field of data-based simulation methods. I’m particularly looking forward to working with outstanding scientists from a range of disciplines and I’m excited about the challenges this newly created professorship brings. In my role as professor, I will be seeking to play a part in the realignment of the Cluster of Excellence and, in particular, to help mold research and training in the simulation and engineering sciences in the long term,” said Felix Fritzen on his appointment.
The Heisenberg Professorship is part of the DFG’s Heisenberg Programme and provides funding for five years. The purpose of the programme is to “enable outstanding researchers who meet all the requirements for appointment to a long-term professorship to prepare for a senior academic role while continuing their research work.”