Autumn HPC School '24

HPC Simulations Specialist

Cluster Administrator

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.

Shuxia Tao is an Associate Professor of Computational Materials Physics within the Department of Applied Physics at TU/e. Her research revolves around the development and application of atomistic and multiscale computational methodologies for the design of novel semiconducting materials for energy and optoelectronic applications. These materials and their applications inherently embody a highly interdisciplinary character, situated at the intersection of Chemistry, Physics, and Materials Science. Computational Materials Science serves as an invaluable tool for probing the intricate interplay between chemical and physical phenomena, thereby affording novel insights into the relationship between the atomistic characteristics of materials and their overall performance.

dr. ir. Joaquin Vanschoren is an Associate Professor of Machine Learning at the Eindhoven University of Technology (TU/e). He aims to deeply understand, explain, and democratize AI to build learning systems that help humanity. He and his team build AI systems that learn continually and assemble themselves to learn faster and better, much like the human brain. He founded OpenML, an open science platform for machine learning, started the NeurIPS Datasets and Benchmarks track to incentivize better training data and evaluations, and works with MLCommons on AI Safety, ML standards, and data-centric AI. He is always eager to collaborate with new people. Do reach out!