Philipp Schlatter (FAU Erlangen-Nürnberg & KTH Stockholm)
Philipp Schlatter (from Zürich, Switzerland) obtained a degree in Mechanical Engineering from the Swiss Federal Institute of Technology (ETH Zürich) in 2001, and a PhD in Fluid Mechanics at the Institute of Fluid Dynamics (IFD) from ETH in 2005. He then moved to the Royal Institute of Technology (KTH) in Stockholm, first as a Postdoc, from 2007-2010 as an assistant professor, from 2010-2018 as associate professor, and from 2019 as full professor at KTH, with special interest in large-scale simulations of turbulent flows, mainly in wall-bounded configurations. In 2014 he was chosen as a Wallenberg Academy Fellow (which was extended in 2018), a prestigious programme with 5+5 year funding. He was also the director of the Linné FLOW Centre at KTH Stockholm, leading the fluid-dynamics community in the Swedish e-Science Research Centre, and the Swedish National Allocation Committee. In 2023 he moved to the Institute of Fluid Mechanics (LSTM) at the Friedrich-Alexander-Universität (FAU) Erlangen-Nürnberg. He is also adjunct professor at the University of Bologna. He is also Associate Editor of the International Journal of Heat and Fluid Flow (IJHFF). The current research involves both large-scale simulations based on highly accurate spectral and spectral-element methods, but also close interaction to experimentalists in an effort to cross-validate simulation and experimental data.
Cevdet Aykanat (Computer Engineering, Bilkent University)
Dr. Cevdet Aykanat is a Professor of Computer Engineering in Bilkent University, Ankara, Turkey. Prof. Aykanat earned his BS and MS degrees in electrical engineering from the Middle East Technical University, and received his PhD in electrical and computer engineering from Ohio State University, where he was a Fullbright scholar, He worked at the Intel Supercomputer Systems Division, Beaverton, Oregon, as a research associate. Since 1989, he has been affiliated with the Department of Computer Engineering, Bilkent University. Research interests of Prof. Aykanat mainly include parallel computing (especially for irregular and unstructured applications), parallel scientific computing and its combinatorial aspects, parallel computer graphics applications, parallel data mining, graph and hypergraph partitioning, load balancing, high-performance information retrieval, parallel and distributed databases, grid computing and high performance computing for big data applications.