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.
Robert WestRobert West is a tenure-track assistant professor of computer science at EPFL, where he heads the Data Science Lab. In his research, he develops and applies techniques in machine learning, computational social science, natural language processing, social network analysis, and data mining. Bob also collaborates closely with the Wikimedia Foundation, in his role as a Wikimedia Research Fellow. Bob’s work has won several awards, including best/outstanding paper awards at ICWSM’21, ICWSM’19, and WWW’13, a best-paper runner-up award at WWW’16, a Google Faculty Research Award, a Facebook Research Award, a Hewlett-Packard Graduate Fellowship, and a Facebook Graduate Fellowship. He is actively involved in the research community, e.g., as an Associate Editor of ICWSM and EPJ Data Science and as a co-founder of the Wiki Workshop (held at WWW and ICWSM) and the Applied Machine Learning Days. Bob received his PhD in Computer Science from Stanford University, his MSc from McGill University, Canada, and his undergraduate degree from Technische Universität München, Germany.[Last updated: 25 Aug 2021]
Babak FalsafiEnseignement et PhD Doctorant·es actuel·les Yuanlong Li, Simla Burcu Harma, Shashwat Shrivastava, Alexandros Poupakis, Shanqing Lin, Ayan Chakraborty, Pooria Poorsarvi Tehrani, Ali Ansari A dirigé les thèses EPFL de Pejman Lotfi Kamran, Sotiria Fytraki, Dejan Novakovic, Stavros Volos, Djordje Jevdjic, Ilknur Cansu Kaynak, Yusuf Onur Koçberber, Javier Picorel Obando, Alexandros Daglis, Mario Paulo Drumond Lages De Oliveira, Arash Pourhabibi Zarandi, Mark Johnathon Sutherland, Siddharth Gupta, Ognjen Glamoc
Paolo IennePaolo Ienne has been a Professor at the EPFL since 2000 and heads the Processor Architecture Laboratory (LAP). Prior to that, he worked for the Semiconductors Group of Siemens AG, Munich, Germany (which later became Infineon Technologies AG) where he was at the head of the Embedded Memories unit in the Design Libraries division. His research interests include various aspects of computer and processor architecture, FPGAs and reconfigurable computing, electronic design automation, and computer arithmetic. Ienne was a recipient of Best Paper Awards at the 20th, 24th, and 28th ACM/SIGDA International Symposia on Field-Programmable Gate Arrays (FPGA), in 2012, 2016 and 2020, at the 19th and 30th International Conference on Field-Programmable Logic and Applications (FPL), in 2009 and 2020, at the International Conference on Compilers, Architectures, and Synthesis for Embedded Systems (CASES), in 2007, and at the 40th Design Automation Conference (DAC), in 2003; many other papers have been candidates to Best Paper Awards in prestigious venues. He has served as general, programme, and topic chair of renown international conferences, including organizing in Lausanne the 26th International Conference on Field-Programmable Logic and Applications (FPL) in 2016. He serves on the steering committee of the IEEE Symposium on Computer Arithmetic (ARITH) and of the International Conference on Field-Programmable Logic and Applications (FPL). Ienne has guest edited a number of special issues and special sections on various topics for IEEE and ACM journals. He is regularly member of program committees of international workshops and conferences in the areas of design automation, computer architecture, embedded systems, compilers, FPGAs, and asynchronous design. He has been an associate editor of ACM Transactions on Architecture and Code Optimization (TACO), since 2015, of ACM Computing Surveys (CSUR), since 2014, and of ACM Transactions on Design Automation of Electronic Systems (TODAES) from 2011 to 2016.
Simone AstoriEnseignement et PhD A co-dirigé les thèses EPFL de Silvia Monari, Alessandro Chioino, Loredana Cumpana
Sanidhya KashyapSanidhya Kashyap is a systems researcher and an assistant professor at the EPFL School of Computer and Communication Sciences (IC). His research focuses on designing systems software that are performant and robust for heterogeneous hardware. He is broadly interested in the area of systems with a particular focus on operating systems, databases, concurrency, scheduling, networks, data analytics, and software testing (fuzzing).
Alexandre SchmidEnseignement et PhD A dirigé les thèses EPFL de Mahsa Shoaran, Wen-Yang Hsu, Reza Ranjandish, Keyvan Farhang Razi, Mohammad Javad Karimi A co-dirigé les thèses EPFL de Milos Stanisavljevic, Neil Joye, Vahid Majidzadeh Bafar, Hossein Afshari, Nikola Katic, Abdulkadir Akin Cours Analog circuits for biochip EE-518 Introduction à la conception analogique CMOS pour des biocapteurs à distance sur puce. Compréhension et la conception de systèmes de biocapteurs actifs et alimentés à distance. Compré
Johanni Michael BreaEnseignement et PhD Doctorant·es actuel·les Aude Maier, Lucas Louis Gruaz, Flavio Martinelli Cours Biological data science II : machine learning BIO-322 Les étudiants comprennent les concepts et méthodes de base d'apprentissage automatique. Ils savent les décrire en termes mathématiques et ils savent les appliquer aux données en utilisant un langage de haut niveau (julia/python/R). Intelligence artificielle et société HUM-286 Ce cours intègre les SHS avec les sciences de l'
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