Mahefa completed his Master’s degree in Mathematics and its Applications from Central European University (CEU) Budapest in June 2020. He started his PhD at Eindhoven University of Technology in January 2021, under the supervision of Jim Portegies. His current research is focused on Mathematical analysis and design of Machine Learning algorithms that automatically discover the explanatory factors of an observed data.
Philipp Horn is a PhD student at TU Eindhoven since October 2020, under the supervision of Professor Barry Koren. His research focuses on embeding physics constraints in the topology of neural networks.
Anna is a PhD student at TU Eindhoven since November 2020 where she works under the supervision of Olga Mula and Wil Schilders. She did her Master’s degree in Applied Mathematics and Informatics at Skolkovo Institute of Science and Technology, Moscow. Her current research interests lie at the intersection of machine learning and model order reduction.
Toby van Gastelen
Toby van Gastelen is a PhD student at the Centrum Wiskunde & Informatica since August 2021, under the supervision of Benjamin Sanderse. He obtained his Master’s degree in Computational Science at the University of Amsterdam. His current research focuses on the construction of physically-consistent neural network based closure models in the field of turbulence modeling.
Giulio is a PhD student at TU Eindhoven since November 2020, under the
supervision of Federico Toschi. His research focuses on
machine learning for analysis and control of complex fluid flows, with a
focus on turbulence modelling.
Veronica Saz Ulibarrena
Veronica is a PhD student at Leiden University since May 2021, under the supervision of Simon Portegies Zwart. She did her Master’s degree in Aerospace Engineering at the Technical University of Delft. Her current research focuses on the application of Artificial Neural Networks to the gravitational N-body problem for applications in astrophysics.
Jim Portegies is an Assistant Professor in the Applied Analysis group of the Centre for Analysis, Scientific computing and Applications (CASA) at Eindhoven University of Technology (TU/e). Jim works in the mathematical fields of analysis, measure theory and geometry, and applies techniques from these fields to problems in machine-learning and artificial intelligence. He has applied techniques from spectral geometry to prove guarantees on performance of nonlinear dimensionality reduction algorithms. Currently, he is investigating how to design algorithms that mimic how humans and animals learn.
Barry Koren received his PhD in aerospace engineering from TU Delft. Prior to his appointment at TU/e, he was full professor Numerical Analysis at Leiden University, full professor Computational Fluid Dynamics at Delft University of Technology (TU Delft), and leader of the research group Modelling, Analysis and Simulation and member of the management team of the Centrum Wiskunde & Informatica (CWI) in Amsterdam. Barry is editor of the Journal of Computational Physics, member of national and international scientific committees and research programs, as well as scientific advisor at CWI. At the TU/e Department of Mathematics and Computer Science, he is currently dean and was vice-dean research for four years. He has authored and edited six books, five special journal issues, and over 150 scientific papers.
Wil Schilders is a Full Professor and Chair of Scientific Computing in the Industry in the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e). His research focuses on numerical linear algebra, indefinite systems, model order reduction, scientific computing, discretisation techniques, boundary element method, singularly perturbed problems, exponential fitting, uniform methods, solution of nonlinear systems, nonlinear variable transformations and numerical methods for the simulation of semiconductor devices and electronic circuits. Wil’s key areas of expertise include computer systems, architectures, networks, numerical analysis, model order reduction, scientific computing and computational science. He has worked in industry for over 30 years and his emphasis has always been on the development of novel mathematical methods for a large variety of industrial challenges. This is also reflected in his current work, with many national and international industrial contacts, and his presidency of ECMI (2010-2011) and EU-MATHS-IN (from 2016).
Benjamin Sanderse is the group leader of the Scientific Computing group. His work focuses on development of numerical methods for uncertainty quantification, for tackling closure problems, for constructing reduced order models, with the overarching theme of using structure-preserving techniques and applying them to solve complex partial differential equations, for example occurring in fluid flow problems. Prior to his tenure track position, he worked at Shell Technology Centre Amsterdam on research and development of multiphase flow simulators in oil and gas applications. His PhD research was on new numerical methods for simulating incompressible flows occurring in wind energy applications, a combined position at Energy research Centre of the Netherlands (ECN) and CWI.
Federico Toschi is full professor at the departments of Applied Physics and of Mathematics and Computer Science at Eindhoven University of Technology (TU/e). His research focuses on the emerging complexity in challenging multi-scale problems at the crossroad between statistical physics, fluid mechanics, soft condensed matter and bio-physics. How do small-scale interactions and forces lead to large-scale complexity and chaos? How to analytically and numerically model complex flow problems? Federico’s research employs experimental, numerical and theoretical methods and covers -amongst others- fluid dynamics turbulence; lagrangian turbulence; thermal convection; complex fluids; soft condensed matter; active matter; crowd dynamics; scientific computing and Lattice Boltzmann methods. Several of Federico’s research topics are strongly interdisciplinary and involve pushing the boundaries of physics across different disciplines. In the computational aspects of his work he pursues innovation of numerical methods as well as large-scale, massively parallel, numerical simulations. His research is embedded in the 4TU Centre of Excellence for Multiscale Phenomena, the JMBC Burgerscentrum for fluid dynamics, and the Eindhoven Multiscale Institute. He served the scientific community by chairing two COST Action on “Particles in turbulence” and “Flowing matter”. He is one of the Founders of the start-up Flow Matters Holding BV.
Simon Portegies Zwart
Simon Portegies Zwart obtained his PhD at Utrecht University. He held several positions at the University of Amsterdam, the University of Tokyo, Boston University and the Massachusetts Institute of Technology. His research interests lie with Computational Gravitational Dynamics, Stellar and Binary Evolution, Galaxy Dynamics, Modeling Dense Stellar Systems, Supermassive Black Holes, Binary Population Synthesis and High-performance Computing. Simon is part of the AMUSE (Astrophysical Multipurpose Software Environment) team. The aim of this project is to provide a software framework for astrophysical simulations in which existing codes from different domains, such as stellar dynamics, stellar evolution, hydrodynamics and radiative transfer can be easily coupled.