Devis TuiaI come from Ticino and studied in Lausanne, between UNIL and EPFL. After my PhD at UNIL in remote sensing, I was postdoc in Valencia (Spain), Boulder (CO) and EPFL, working on model adaptation and prior knowledge integration in machine learning. In 2014 I became Research Assistant Professor at University of Zurich, where I started the 'multimodal remote sensing' group. In 2017, I joined Wageningen University (NL), where I was professor of the GeoInformation Science and Remote Sensing Laboratory. Since 2020, I joined EPFL Valais, to start the ECEO lab, working at the interface between Earth observation, machine learning and environmental sciences.
Alexander MathisAlexander studied pure mathematics with a minor in logic and theory of science at the Ludwig Maximilians University in Munich. For his PhD also at LMU, he worked on optimal coding approaches to elucidate the properties of grid cells. As a postdoctoral fellow with Prof. Venkatesh N. Murthy at Harvard University and Prof. Matthias Bethge at Tuebingen AI, he decided to study olfactory behaviors such as odor-guided navigation, social behaviors and the cocktail party problem in mice. During this time, he increasingly got interested sensorimotor behaviors beyond olfaction and started working on proprioception, motor adaption, as well as computer vision tools for measuring animal behavior.
In his group, he is interested in elucidating how the brain gives rise to adaptive behavior. One of the major goals is to synthesize large datasets into computationally useful information. For those purposes, he develops algorithms and systems to analyze animal behavior (e.g. DeepLabCut), neural data, as well as creates experimentally testable computational models.
Martin JaggiMartin Jaggi is a Tenure Track Assistant Professor at EPFL, heading the Machine Learning and Optimization Laboratory. Before that, he was a post-doctoral researcher at ETH Zurich, at the Simons Institute in Berkeley, and at École Polytechnique in Paris. He has earned his PhD in Machine Learning and Optimization from ETH Zurich in 2011, and a MSc in Mathematics also from ETH Zurich.
Touradj EbrahimiTouradj EBRAHIMI received his M.Sc. and Ph.D., both in Electrical Engineering, from the Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland, in 1989 and 1992 respectively. In 1993, he was a research engineer at the Corporate Research Laboratories of Sony Corporation in Tokyo, where he conducted research on advanced video compression techniques for storage applications. In 1994, he served as a research consultant at AT&T Bell Laboratories working on very low bitrate video coding. He is currently Professor at EPFL heading its Multimedia Signal Processing Group. He is also the Convenor of JPEG standardization Committee. He was also adjunct Professor with the Center of Quantifiable Quality of Service at Norwegian University of Science and Technology (NTNU)from 2008 to 2012.
Prof. Ebrahimi has been the recipient of various distinctions and awards, such as the IEEE and Swiss national ASE award, the SNF-PROFILE grant for advanced researchers, Four ISO-Certificates for key contributions to MPEG-4 and JPEG 2000, and the best paper award of IEEE Trans. on Consumer Electronics . He became a Fellow of the international society for optical engineering (SPIE) in 2003. Prof. Ebrahimi has initiated more than two dozen National, European and International cooperation projects with leading companies and research institutes around the world. He is a co-founder of Genista SA, a high-tech start-up company in the field of multimedia quality metrics. In 2002, he founded Emitall SA, start-up active in the area of media security and surveillance. In 2005, he founded EMITALL Surveillance SA, a start-up active in the field of privacy and protection. He is or has been associate Editor with various IEEE, SPIE, and EURASIP journals, such as IEEE Signal Processing Magazine, IEEE Trans. on Image Processing, IEEE Trans. on Multimedia, EURASIP Image Communication Journal, EURASIP Journal of Applied Signal Processing, SPIE Optical Engineering Magazine. Prof. Ebrahimi is a member of Scientific Advisory Board of various start-up and established companies in the general field of Information Technology. He has served as Scientific Expert and Evaluator for Research Funding Agencies such as those of European Commission, The Greek Ministry of Development, The Austrian National Foundation for Scientific Research, The Portuguese Science Foundation, as well as a number of Venture Capital Companies active in the field of Information Technologies and Communication Systems. His research interests include still, moving, and 3D image processing and coding, visual information security (rights protection, watermarking, authentication, data integrity, steganography), new media, and human computer interfaces (smart vision, brain computer interface).
He is the author or the co-author of more than 200 research publications, and holds 14 patents. Prof. Ebrahimi is a member of IEEE, SPIE, ACM and IS&T.
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http://mmspl.epfl.ch Lenka ZdeborováLenka Zdeborová is a Professor of Physics and of Computer Science in École Polytechnique Fédérale de Lausanne where she leads the Statistical Physics of Computation Laboratory. She received a PhD in physics from University Paris-Sud and from Charles University in Prague in 2008. She spent two years in the Los Alamos National Laboratory as the Director's Postdoctoral Fellow. Between 2010 and 2020 she was a researcher at CNRS working in the Institute of Theoretical Physics in CEA Saclay, France. In 2014, she was awarded the CNRS bronze medal, in 2016 Philippe Meyer prize in theoretical physics and an ERC Starting Grant, in 2018 the Irène Joliot-Curie prize, in 2021 the Gibbs lectureship of AMS. She is an editorial board member for Journal of Physics A, Physical Review E, Physical Review X, SIMODS, Machine Learning: Science and Technology, and Information and Inference. Lenka's expertise is in applications of concepts from statistical physics, such as advanced mean field methods, replica method and related message-passing algorithms, to problems in machine learning, signal processing, inference and optimization. She enjoys erasing the boundaries between theoretical physics, mathematics and computer science.
