FAU MoD Workshop G. Fantuzzi / D. Martonová

Date: Wed. December 10, 2025
Event: FAU MoD Workshop
Organized by: FAU MoD, the Research Center for Mathematics of Data at Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany)

Session 01: 11:30H
Lyapunov meets Koopman: a new approach to data-driven analysis of nonlinear dynamics
Speaker: Prof. Dr. Giovanni Fantuzzi
Affiliation: FAU MoD, Research Center for Mathematics of Data | FAU DCN-AvH at Friedrich-Alexander-Universität Erlangen-Nürnberg
Abstract. Lyapunov frameworks have been used for decades to analyze the performance of nonlinear dynamical systems with known mathematical models. The Koopman operator framework has instead recently gained popularity for studying nonlinear dynamics from data. This talk will explain how these two frameworks can be unified into a groundbreaking data-driven Koopman-Lyapunov approach for analyzing nonlinear dynamics, which can answer a much wider range of dynamical systems questions compared to classical Koopman methods alone. I will also discuss perspectives and open challenges related to the implementation and mathematical analysis of this Koopman-Lyapunov approach.

  
Session 02: 12:05H
Data-driven constitutive modeling for soft biological tissues
Speaker: Dr. Denisa Martonová
Affiliation: FAU MoD, Research Center for Mathematics of Data | Institute of Applied Mechanics at Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany)
Abstract. An accurate description of mechanical behavior in biological tissues relies on the formulation of suitable constitutive models. This talk will explain how data-driven approaches can automate the discovery of such models directly from experimental measurements. We introduce invariant-based and principal-stretch-based constitutive neural networks that embed physical constraints and recover interpretable formulations for hyperelastic materials. We then extend this concept to generalized-invariant-based constitutive neural networks, which simultaneously learn both the invariant representation and the underlying model. Finally, we outline a complementary database-driven method that bypasses numerical optimization and rapidly identifies constitutive behavior through pattern recognition. Together, these approaches illustrate how automated, physics-embedded model discovery can enhance modeling in biomechanics and beyond.

OUR SPEAKERS

Giovanni Fantuzzi is a W1 Professor in the Department of Mathematics at Friedrich-Alexander-Universität (FAU) Erlangen-Nürnberg. Before joining FAU, Prof. Fantuzzi held an Imperial College Research Fellowship in the Department of Aeronautics, where he also received a PhD and a Master Eng. in Aeronautics degrees. Alongside his PhD, he held a research position in Engineering Science at the University of Oxford. He was awarded a Geophysical Fluid Dynamics Fellowship at WHOI (2015) and an EPSRC Doctoral Prize Fellowship (2018).
His work spans optimization, dynamical systems, fluid mechanics, and partial differential equations (PDEs), in particular, nonlinear differential equations using a mix of mathematical analysis and numerical tools for convex optimization.

Denisa Martonová is a researcher at the Institute of Applied Mechanics (LTM) at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). She also completed her doctoral studies at FAU, where her research focused on computational modeling and simulation of myocardial tissue. Her current work focuses on data-driven constitutive modeling, with a particular emphasis on soft biological materials and hyperelastic tissue behavior.

See poster

AUDIENCE

This is a hybrid event (On-site/online) open to: Public, Students, Postdocs, Professors, Faculty, Alumni and the scientific community all around the world.

WHEN

Wed. December 10, 2025 at 11:30H (Berlin time)

WHERE

On-site / Online

 
Shortlink to share this event: https://go.fau.de/1cca-

This event @LinkedIn

 
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