Michaël UnserExpertise
Image Processing, Medical Imaging, Biological Imaging, Wavelets, Splines, Multiresolution
Michael Unser is Full Professor with EPFL’s school of Engineering and the academic director of EPFL's Center for Imaging, Lausanne, Switzerland. His primary areas of investigation are signal processing, biomedical imaging and applied functional analysis. He is internationally recognized for his research contributions to sampling theory, wavelets, the use of splines for image processing, stochastic processes,
Mats Julius StensrudTeaching & PhD PhD Students Ignacio Gonzalez Perez, Gellért Géza Perényi, Lorenzo Gasparollo, Julien David Laurendeau Past EPFL PhD Students Matias Janvin, Amit Sawant Courses Causal thinking MATH-352 This course will give a unified presentation of modern methods for causal inference. We focus on concepts, and we will present examples and ideas from various scientific disciplines, including medicine, computer science, engineering, economics and epidemiology. Probability and statistics (
Sébastien OttTeaching & PhD Courses Large deviations MATH-533 An introduction to the theory of large deviations, focusing on studying examples and deriving the general theory from the ideas developed in the examples. Probability and statistics (for IC) MATH-232
Gregor JotzuGregor Jotzu is heading the Dynamic Quantum Materials Laboratory (DQML) at EPFL. His research concerns the control of quantum materials using intense low-frequency laser pulses and the dynamics of order formation in strongly correlated quantum systems.After reading physics at the University of Oxford, he became the 2009/2010 Michael von Clemm Fellow at Harvard University. He received his doctorate from ETH Zurich, where he studied quantum magnetism and driving-induced order using ultracold atoms in optical
Sofia Charlotta OlhedeI am a professor of Statistics at EPFL. I did my PhD in Mathematics at Imperial College London, and graduated in 2003. I was an assistant professor (lecturer) at Imperial College London 2002-2006, and an associate professor (senior lecturer) 2006-2007. In 2007 I moved to University College London and became a full professor. I moved to EPFL in 2019, and in 2018 I became an Institute of Mathematical Statistics Fellow with citation “For seminal contributions to the theory and application of large and heteroge
André AnjosExpertise
Reproducible ResearchPattern RecognitionImage ProcessingMachine LearningBiometrics
Short bio
André Anjos received his Ph.D. degree in signal processing in 2006 studying the application of neural nets and statistical methods for particle recognition in the context of High-Energy Physics experiments at Large Hadron Collider at CERN, Switzerland. He joined the Idiap Research Institute in 2010 where he works with biosignal processing and biometrics applications. He currently heads the Biosignal Proces
Philippe MüllhauptExpertise
Nonlinear Control (Geometry and Algebra)Classical DynamicsRoboticsStatistics
Mission
Provide rigorous technical and scientific training in nonlinear control, classical mechanics, and statistical theory
Current Work
Research and teaching in the fields of control theory, statistics, dynamical systems, and general mechanics.
Philippe Mullhaupt received his Diplôme d Education Ing�nieur | Electricit� 1993 – 1993 EPFL DEA | Automatique et Traitement du Signal 199
Rajita Ramesh ChandakExpertise
Nonparametric estimation, statistical inference, theory of machine learning
Teaching & PhD Courses Nonparametric estimation and inference MATH-524 Nonparametric models are used to identify a wide range of relationships within data. This course gives a graduate-level overview of nonparametric statistical estimation and inference theory. Statistical inference MATH-562 Inference from the particular to the general based on probability models is central to the statistica
Linda MarchandTeaching & PhD Courses Applied statistics MATH-516 The course will provide an overview of everyday challenges in applied statistics through case studies. Students will learn how to use core statistical methods and their extensions, and will use computational and problem-solving tools to provide reproducible solutions for the problems presented. Bioinformatic Analysis of RNA-sequencing (Fall) BIO-693(a) Bioinformatic Analysis of RNA-sequencing (Spring) BIO-693(b)
Sabine SüsstrunkProf. Dr. Sabine Süsstrunk leads the Image and Visual Representation Lab in the School of Computer and Communication Sciences (IC) at EPFL since 1999. From 2015-2020, she was also the first Director of the Digital Humanities Institute (DHI), College of Humanities (CdH). Her main research areas are in computational photography, computational imaging, color image processing and computer vision, machine learning, and computational image quality and aesthetics. Sabine has authored and co-authored over 200 publications, of which 7 have received best paper/demo awards, and holds over 10 patents. Sabine served as chair and/or committee member in many international conferences on image processing, computer vision, and image systems engineering. She is President of the Swiss Science Council SSC, Founding Member and Member of the Board (President 2014-2018) of the EPFL-WISH (Women in Science and Humanities) Foundation, Member of the Board of the SRG SSR (Swiss Radio and Television Corporation), and Member of the Board of Largo Films. She received the IS&T/SPIE 2013 Electronic Imaging Scientist of the Year Award for her contributions to color imaging, computational photography, and image quality, and the 2018 IS&T Raymond C. Bowman and the 2020 EPFL AGEPoly IC Polysphere Awards for excellence in teaching. Sabine is a Fellow of IEEE and IS&T.
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