Sophia BeckerExpertise
Computational and theoretical neuroscienceReinforcement learning
Mika Tapani GöösEnseignement et PhD Doctorant·es actuel·les Valentin Imbach, Ziyi Guan, Artur Riazanov, Anastasiia Sofronova, Weiqiang Yuan A dirigé les thèses EPFL de Maystre Gilbert Théodore Cours Computational complexity CS-524 En théorie de la complexité, nous étudions les ressources nécessaires à résoudre des problèmes et les relations entre différents modèles de calcul.Ce cours donne une meilleure connaissance de la complexité informatique et aborde les questions ouvertes fondamentales.
Kevin SivulaEnseignement et PhD Doctorant·es actuel·les Odile Louise Andres, Arthur Eliot Bouchez, Benjamin Goldman, Nicolas Johannes Diercks, Aurélie Fanny Marie Célérien, Jiajun Li, Louise Marie Foltzer-De Cian, Melanie Victoria Johanning, Nils William Laurent Golay A dirigé les thèses EPFL de Andrea Gasperini, Pauline Bornoz, Xavier Adrian Jeanbourquin, Xiaoyun Yu, Mathieu Steven Prévot, Muhammad Aiman Bin Rahmanudin Hamdan, Nhât-Tân Vuong, Yongpeng Liu, Arvindh Sekar, Barbara Alexandra Primera Darwich, Rebekah An
Michaël UnserExpertise
Image Processing Medical Imaging Biological Imaging Wavelets Splines Multiresolution
Enseignement et PhD Doctorant·es actuel·les Youssef Haouchat, Vincent Patrick Lawrence Guillemet, Bassam El Rawas, Stanislas Ducotterd, Mehrsa Pourya, Zhiyuan Hu A dirigé les thèses EPFL de Stefan Horbelt, Jan Kybic, Maria Arrate Munoz Barrutia, Manuela Feilner, Slavica Jonic, Mathews Jacob, Michael Liebling, Michael Sühling, Muthuvel Arigovindan, François Aguet, Cédric Vonesch, Ildar Khalidov, Sathish Ramani, F
Simone DeparisExpertise
Simone Deparis est professeur à l’EPFL, spécialisé en mathématiques appliquées, analyse numérique et didactique des mathématiques à l’université. Ses recherches portent à la fois sur la modélisation computationnelle pour les applications biomédicales et sur l’innovation pédagogique, avec un accent sur l’équité, l’auto-efficacité et la réforme de l’évaluation dans les grands cursus scientifiques.
Mission
Mes recherches portent sur les mathématiques appliquées et les sciences de l’apprentissage. En
Michael Christoph GastparMichael Gastpar is a (full) Professor at EPFL. From 2003 to 2011, he was a professor at the University of California at Berkeley, earning his tenure in 2008. He received his Dipl. El.-Ing. degree from ETH Zürich, Switzerland, in 1997 and his MS degree from the University of Illinois at Urbana-Champaign, IL, USA, in 1999. He defended his doctoral thesis at EPFL on Santa Claus day, 2002. He was also a (full) Professor at Delft University of Technology, The Netherlands. His research interests are in network information theory and related coding and signal processing techniques, with applications to sensor networks and neuroscience. He is a Fellow of the IEEE. He is the co-recipient of the 2013 Communications Society & Information Theory Society Joint Paper Award. He was an Information Theory Society Distinguished Lecturer (2009-2011). He won an ERC Starting Grant in 2010, an Okawa Foundation Research Grant in 2008, an NSF CAREER award in 2004, and the 2002 EPFL Best Thesis Award. He has served as an Associate Editor for Shannon Theory for the IEEE Transactions on Information Theory (2008-11), and as Technical Program Committee Co-Chair for the 2010 International Symposium on Information Theory, Austin, TX.
Simon Elias BibriExpertise
• Sustainable cities• Smarter eco-cities• Sustainable smart cities• Artificial Intelligence of Things (AIoT) • Generative Artificial Intelligence of Things (GAIoT)• Foundation Models (FMs) • Quantum Generative Artificial Intelligence (QGAI)• Urban Digital Twins (UDTs)• Urban Brain (UB) • Smart Circular Metabolism• Urban planning and design• Environmental sustainability and climate resilience• Sustainable smart energy• Sustainable smart transportation• Sustainable smart waste and water management•
Laura GrigoriExpertise
Numerical linear algebra, deterministic and randomized algorithmsHigh performance computing for scientific applicationsHigh dimensional problems and tensor computationsCombinatorial scientific computingMathematical Software
Enseignement et PhD Doctorant·es actuel·les Israa Fakih, Zhipeng Xue, Andrea Di Antonio, Mariana Graciela Martinez Aguilar, Guifré Sánchez i Serra Cours Numerical analysis and computational mathematics MATH-456 Ce cours offre une introduction au calcul scienti
Patrick ThiranPatrick Thiran is a full professor in network and systems theory at the School of Computer and Communication Sciences at EPFL. He holds an electrical engineering degree from the Université Catholique de Louvain, Louvain-la-Neuve, Belgium, an M.Sc. degree in electrical engineering from the University of California at Berkeley, USA, and he received the PhD degree from EPFL, in 1996. He became an adjunct professor in 1998, an assistant professor in 2002, an associate professor in 2006 and a full professor in 2011. He was with Sprint Advanced Technology Labs in Burlingame, California, in 2000-01.
His research interests are in communication and social networks, performance analysis and stochastic models. He is currently active in the analysis and design of wireless and PLC networks (scaling laws, medium access control), in network monitoring (network tomography, multi-layer networks), and data-driven network science. He also contributed to network calculus and to the theory of locally coupled neural networks and self-organizing maps.
He served as an associate editor for the IEEE Transactions on Circuits and Systems in 1997-99 and for the IEEE/ACM Transactions on Networking in 2006-10. He is currently on the editorial board of the IEEE Journal on Selected Areas in Communication. He is/was on the program committee of different conferences in networking, including ACM Sigcomm, Sigmetrics, IMC, CoNext and IEEE Infocom. He was TPC chair of AMC IMC 2011 and CoNext 2012. He is a Fellow of the Belgian American Educational Foundation and of the IEEE. He received the 1996 EPFL Doctoral Prize and the 2008 Crédit Suisse Teaching Award.
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.
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