Assistant Professor with Habilitation at the Department of Mechanical Engineering (Section of Mathematics), Faculty of Engineering, University of Porto (FEUP), and a researcher at the Centre of Mathematics, University of Minho, Portugal. He received his PhD in Science and Engineering of Polymers and Composites from the University of Minho in 2012, a Ph.D. in Mathematics from the University of Chester in 2019, and was a visiting researcher at MIT in 2016 and 2017. His current research interests are numerical analysis, applied mathematics, partial and fractional differential equations, mathematical modelling, computational mechanics, computational fluid dynamics, complex viscoelastic flows, rheology, anomalous diffusion, and machine learning.
Cecília CoelhoPhD in Mathematics and currently Postdoctoral Researcher and Senior Scientist Leader of “Material Science and Spacial Models” at the Professorship Computer Science in Mechanical Engineering, Helmut Schmidt University, Hamburg, Germany. Her current research focuses on enhancing the performance of real-world systems modelling (physics, biology, chemistry, finance and engineering) by exploring the symbiosis of differential equations and neural networks and the integration of expert knowledge, in the form of explicit constraints, into neural networks.
Andrzej DulnyResearcher at the Data Science Chair at the University of Würzburg, where he has been part of the DMIR Research Group since 2021. He received his M.Sc. in Mathematics from the University of Würzburg and his B.Sc. from the Jagiellonian University in Cracow. His current research lies at the intersection of machine learning and physics, with a focus on developing deep learning methods for modeling and predicting the evolution of physical systems. He is particularly interested in Physics-Informed Neural Networks, Neural ODEs, Graph Neural Networks, and Transformer-based models for spatial data, with special emphasis on handling non-grid and low-resolution data.