The [ML-DE] Workshop on “Machine Learning Meets Differential Equations: From Theory to Applications” is organized by a group of distinguished researchers dedicated to exploring the synergies between machine learning and differential equations.

Cecília Coelho

Centre of Mathematics, University of Minho, Portugal
Email: cmartins@cmat.uminho.pt
Cecília is pursuing a PhD in Mathematics, focusing on the integration of differential equations and neural networks to enhance modeling of real-world systems across various domains. Her research interests span the incorporation of expert knowledge into neural networks and the development of hybrid models.

Luís Ferrás

Department of Mechanical Engineering, University of Porto, Portugal
Email: lferras@fe.up.pt
An Assistant Professor and researcher, Luís specializes in numerical analysis, applied mathematics, and the intersection with machine learning. He has a strong track record of organizing international workshops and conferences aimed at advancing research in these areas.

Fernanda Costa

Centre of Mathematics, University of Minho, Portugal
Email: mfc@math.uminho.pt
As an Associate Professor, Fernanda’s research focuses on optimization, machine learning techniques, and their applications in mathematical modeling and applied mathematics. She has been instrumental in organizing events that bridge these disciplines.

Bernd Zimmering

Institute for Automation Technology, Helmut-Schmidt-University, Germany
Email: bernd.zimmering@hsu-hh.de
Bernd’s PhD research is dedicated to leveraging neural Ordinary Differential Equations (ODEs) for improving cyber-physical systems. His work explores sophisticated time-continuous algorithms and their practical applications.

Oliver Niggemann

Institute for Automation Technology, Helmut-Schmidt-University, Germany
Email: oliver.niggemann@hsu-hh.de
Oliver, a Full Professor, focuses on the application of AI and machine learning in cyber-physical systems. His research aims to enhance system performance and reliability through innovative computational approaches.

The organizing team brings together a wealth of experience in both theoretical and applied aspects of machine learning and differential equations, ensuring a comprehensive and insightful workshop.