Jean-Paul Richard KneibEnseignement et PhD Doctorant·es actuel·les Oliver Pineda Suarez, Robert Daniel Kincaid, Ethan Daniel Tregidga, Belén Yu Irureta-Goyena Chang, Elisabeth Andréa Cécile Rachith, Shengyu He, Aurélien Thomas Mathieu Verdier, Timour Jestin A dirigé les thèses EPFL de Markus Rexroth, Luzius Gregor Kronig, Christoph Ernst René Schäfer, Vasileios Angelopoulos, Michaël Juillard, Amélie Tamone, Andrei Variu, Yoan Rappaz, Anne-Marlene Rüede, Jiaxi Yu, Daniel Felipe Forero Sanchez, Beauchesne Benjamin Emmanuel Nicola
Yves RevazYves Revaz est maître d'enseignement et de recherche au laboratoire d'astrophysique (LASTRO) de l'EPFL. Après des études à l'EPFL, il a soutenu une thèse de doctorat intitulée: "Dynamique des régions externes des galaxies spirales et contraintes sur la matière noire" à l'Observatoire de Genève, sous la direction du Prof. Daniel Pfenniger. Il a ensuite travaillé à l'Observatoire de Paris, au LERMA (Laboratoire d'Etudes du Rayonnement et de la Matière en Astrophysique et Atmosphères) sous la supervision de la Prof. Françoise Combes et s'est intéressé aux écoulement froids dans les amas de galaxies. Il a rejoint le LASTRO en 2007, où, en collaboration avec la Prof. Pascale Jablonka, il a développé un nouveau code TreePM/SPH chemo-dynamique appelé GEAR, dans le but d'étudier l'évolution chimique des galaxies. Sa recherche se focalise actuellement sur l'évolution des galaxies naines et leur lien avec la cosmologie. Yves Revaz et aussi l'auteur de pNbody, une librairie python parallélisée dédiée à l'analyse de larges systèmes N-corps.
Herbert SheaEnseignement et PhD Doctorant·es actuel·les Myoung Ju Kim, Xintong Tong, Huapeng Zhang, Rohit Kadungamparambil John, Yichi Luo, Lucas Aurélien Jourdan, Ayana Mizutani, Donghyun Kim A dirigé les thèses EPFL de Michael Bodendorfer, Renato Krpoun, Samuel Rosset, Muhamed Niklaus, Kaustav Ghose, Samin Akbari, Vinu Lalgudi Venkatraman, Luc Maffli, Simon Dandavino, Tobias Bandi, Subha Chakraborty, Pietro Romano, Alexandre Poulin, Marianna Fighera, Nadine Besse, Alexis Pierre Henri Marette, Reto Wiesendanger, Fr
Mikhail ChapochnikovEnseignement et PhD A dirigé les thèses EPFL de Ewald Rössl, Katarzyna Zuleta Estrugo, Yannis Burnier, Stephen Clark, Matthias Schmid, Claude Becker, Daniel Zenhäusern, Amaury Magnin, Laurent Canetti, Georgios Karananas, Andrey Shkerin, Adrien Florio
Michaela HirschmannEnseignement et PhD Doctorant·es actuel·les Patrick Hirling, Jonathan Petersson, Lucie Scharré Cours Astrophysics III : galaxy formation and evolution PHYS-465 Ce cours décrit les propriétés observationnelles des galaxies ainsi que les processus physiques à l'origine de leur évolutiontels qu'ils sont perçus par les modèles théoriques et numériques. Physique générale : thermodynamique (anglais) PHYS-106(en) Donner à l'étudiant les notions de base nécessaires à la compréhensi
David Atienza AlonsoDavid Atienza Alonso is an associate professor of EE and director of the Embedded Systems Laboratory (ESL) at EPFL, Switzerland. He received his MSc and PhD degrees in computer science and engineering from UCM, Spain, and IMEC, Belgium, in 2001 and 2005, respectively. His research interests include system-level design methodologies for multi-processor system-on-chip (MPSoC) servers and edge AI architectures. Dr. Atienza has co-authored more than 350 papers, one book, and 12 patents in these previous areas. He has also received several recognitions and award, among them, the ICCAD 10-Year Retrospective Most Influential Paper Award in 2020, Design Automation Conference (DAC) Under-40 Innovators Award in 2018, the IEEE TCCPS Mid-Career Award in 2018, an ERC Consolidator Grant in 2016, the IEEE CEDA Early Career Award in 2013, the ACM SIGDA Outstanding New Faculty Award in 2012, and a Faculty Award from Sun Labs at Oracle in 2011. He has also earned two best paper awards at the VLSI-SoC 2009 and CST-HPCS 2012 conference, and five best paper award nominations at the DAC 2013, DATE 2013, WEHA-HPCS 2010, ICCAD 2006, and DAC 2004 conferences. He serves or has served as associate editor of IEEE Trans. on Computers (TC), IEEE Design & Test of Computers (D&T), IEEE Trans. on CAD (T-CAD), IEEE Transactions on Sustainable Computing (T-SUSC), and Elsevier Integration. He was the Technical Program Chair of DATE 2015 and General Chair of DATE 2017. He served as President of IEEE CEDA in the period 2018-2019 and was GOLD member of the Board of Governors of IEEE CASS from 2010 to 2012. He is a Distinguished Member of ACM and an IEEE Fellow.
Emma Elizabeth TolleyI studied the universe at the smallest scales at the Large Hadron Collider, now we're getting ready to study it at the largest scales with the Square Kilometer Array. My research focuses on developing high-performance computing and new data science techniques to image and analyse the radio sky.
Enseignement et PhD Doctorant·es actuel·les Markus Johan Bredberg, Ashutosh Kumar Mishra A co-dirigé les thèses EPFL de Shreyam Parth Krishna Cours Physique générale : mécanique (classe inversée en anglais)
Pierre VandergheynstPierre Vandergheynst received the M.S. degree in physics and the Ph.D. degree in mathematical physics from the Université catholique de Louvain, Louvain-la-Neuve, Belgium, in 1995 and 1998, respectively. From 1998 to 2001, he was a Postdoctoral Researcher with the Signal Processing Laboratory, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland. He was Assistant Professor at EPFL (2002-2007), where he is now a Full Professor of Electrical Engineering and, by courtesy, of Computer and Communication Sciences. As of 2015, Prof. Vandergheynst serves as EPFL’s Vice-Provost for Education. His research focuses on harmonic analysis, sparse approximations and mathematical data processing in general with applications covering signal, image and high dimensional data processing, computer vision, machine learning, data science and graph-based data processing. He was co-Editor-in-Chief of Signal Processing (2002-2006), Associate Editor of the IEEE Transactions on Signal Processing (2007-2011), the flagship journal of the signal processing community and currently serves as Associate Editor of Computer Vision and Image Understanding and SIAM Imaging Sciences. He has been on the Technical Committee of various conferences, serves on the steering committee of the SPARS workshop and was co-General Chairman of the EUSIPCO 2008 conference. Pierre Vandergheynst is the author or co-author of more than 70 journal papers, one monograph and several book chapters. He has received two IEEE best paper awards. Professor Vandergheynst is a laureate of the Apple 2007 ARTS award and of the 2009-2010 De Boelpaepe prize of the Royal Academy of Sciences of Belgium.
David Richard HarveyEnseignement et PhD Doctorant·es actuel·les Ethan Daniel Tregidga, Felix Francisco Vecchi Cours Lecture series on scientific machine learning PHYS-754 Ce cours présente des travaux sur la façon dont les questions scientifiques peuvent être abordées à l'aide de l'apprentissage automatique. L'apprentissage automatique permet d'extraire des connaissances à partir de données de manière automatisée. Nous apprendrons à partir d'exemples concrets.
