2025 - KoMSO Academy

Stefania Fresca is Assistant Professor in Numerical Analysis at MOX (Laboratory for Modeling and Scienti?c Computing) - Department of Mathematics at Politecnico di Milano, Italy.

In 2017, she started her Ph.D. in the ¡°Mathematical Models and Methods in Engineering¡± Program at Politecnico di Milano, in the framework of the ERC Advanced Grant Project iHEART led by Prof. Al?o Quarteroni and devoted to cardiac modeling. After obtaining her Ph.D. Degree cum laude in 2021, she was recognized the Runner-up Best Ph.D. Award in Biomedical Engineering at the 7th International Conference on Computational & Mathematical Biomedical Engineering (CMBE22). Following her Ph.D., she spent two years as Post-Doctoral Research Fellow at MOX. From September 2024 to March 2025, she visited the Departments of Computer Science, and Applied Mathematics and Theoretical Physics at University of Cambridge, hosted by Prof. Pietro Li¨° and Prof. Carola Sch?nlieb.

Her research interests and expertise include scienti?c machine learning, reduced order modeling (data dimensionality reduction), deep learning, digital twins, and numerical approximation of PDEs, with several applications to engineering problems.

Felix D?ppel is a postdoctoral researcher at the Politecnico di Milano, Italy. His main research topic is the development of physically plausible machine learning models for the efficient description of multiscale (surface) reactive systems, and the discovery of kinetic mechanisms.

During his studies in chemistry at the Technical University of Darmstadt he was awarded multiple fellowships, including the German Academic Scholarship for young people with outstanding talents. He earned his Ph.D. on "Physics-Enhanced Machine Learning for Chemical Kinetics" in Darmstadt with summa cum laude.

In 2024 he joined the Laboratory of Catalysis and Catalytic Processes at PoliMi hosted by Prof. Mauro Bracconi and Prof. Matteo Maestri, where he was awarded the MSCA Seal of Excellence fellowship.

Alexander Fuchs is a research engineer at Bosch Research. His main research area includes multiphysics modeling across multiple time and length scales enhanced by machine learning techniques. 

Dr. Fuchs studied mechanical engineering in Dresden and obtained his doctorate in 2020 from TU Dresden in the field of computational engineering. In his research, he was working on multiscale modeling of composite materials using machine learning techniques. 

After finishing his Ph.D., he joined Bosch in 2021, where he mainly works on modeling of electrochemical surface reactions with focus on corrosion processes as well as the industrialization of these models.

Derick Nganyu Tanyu completed his Ph.D. at the University of Bremen in 2023 under the supervision of Prof. Dr. Peter Maass at the Zentrum f¨¹r Industriemathematik (ZeTeM). His doctoral research focused on the intersection of deep learning, partial differential equations, and inverse problems. He explored scientific machine learning techniques for PDE-based inverse problems, with applications in areas such as Electrical Impedance Tomography (EIT) and continuum mechanics.

Following his Ph.D., he held a postdoctoral position in the Workgroup Inverse Problems and Imaging at ZeTeM, working with Prof. Dr. Dirk Lorenz. His research focused on the use of Physics-Informed Neural Networks in continuum micromechanics, with applications in structural health monitoring.

He previously studied at ?cole Nationale Sup¨¦rieure Polytechnique in Yaound¨¦, Cameroon, and at the African Institute for Mathematical Sciences (AIMS) in Ghana.

He is currently working as a Developer at SAP.

Uwe Iben is a Chief Expert for Applied Mathematics at Bosch Research.
His main research aeras includes AI methods for solving of ODEs and PDEs as surrogate models. He has joined the Robert Bosch GmbH in 1999 as a simulation engineer. He worked 15 years on the field of multi-phase flow and cavitation as a project leader and Chief expert. From 2016 till 2020 he became the head of Research and Technology Offices in Saint Petersburg/Russia.
Dr. Iben studied mathematics at Moscow State University and Technical University of Dresden. After his PhD in the field of numerical mathematics, he worked as a PostDoc at Otto-von-Guericke University, Magdeburg. In 2003, he received his doctorate in the field of modeling of cavitating flow phenomena from Otto-von-Guericke University Magdeburg, Germany. He became an honorary professor at the University of Stuttgart in 2017 where he gives lectures on multi-phase flow phenomena.

Peter Maass (Professor for Applied Mathematics at the Center for Industrial Mathematics at University of Bremen, ZeTeM). His main research areas include inverse problems, parameter identification, and since several years deep learning.

Prof. Maass studied mathematics in Karlsruhe, Cambridge and Heidelberg and obtained his doctorate in 1988 from TU Berlin as well as his habilitation in mathematics from Saarland University in 1993. Peter Maass was a full professor at Potsdam University from 1993 -1999 before becoming director of ZeTeM.
He spent several longterm research visits as guest professor or researcher at leading international universities including Paris, Berkeley, Boston and Cambridge.