Personnes associées (18)
Paolo Ienne
Paolo 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.
Babak Falsafi
Babak is a Professor in the School of Computer and Communication Sciences and the founding director of the EcoCloud, an industrial/academic consortium at EPFL investigating scalable data-centric technologies. He has made numerous contributions to computer system design and evaluation including a scalable multiprocessor architecture which was prototyped by Sun Microsystems (now Oracle), snoop filters and memory streaming technologies that are incorporated into IBM BlueGene/P and Q and ARM cores, and computer system performance evaluation methodologies that have been in use by AMD, HP and Google PerKit . He has shown that hardware memory consistency models are neither necessary (in the 90's) nor sufficient (a decade later) to achieve high performance in multiprocessor systems. These results eventually led to fence speculation in modern microprocessors. His latest work on workload-optimized server processors laid the foundation for the first generation of Cavium ARM server CPUs, ThunderX. He is a recipient of an NSF CAREER award, IBM Faculty Partnership Awards, and an Alfred P. Sloan Research Fellowship. He is a fellow of IEEE and ACM.
Jean-Philippe Thiran
Jean-Philippe Thiran was born in Namur, Belgium, in August 1970. He received the Electrical Engineering degree and the PhD degree from the Université catholique de Louvain (UCL), Louvain-la-Neuve, Belgium, in 1993 and 1997, respectively. From 1993 to 1997, he was the co-ordinator of the medical image analysis group of the Communications and Remote Sensing Laboratory at UCL, mainly working on medical image analysis. Dr Jean-Philippe Thiran joined the Signal Processing Institute (ITS) of the Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland, in February 1998 as a senior lecturer. He was promoted to Assistant Professor in 2004, to Associate Professor in 2011 and is now a Full Professor since 2020. He also holds a 20% position at the Department of Radiology of the University of Lausanne (UNIL) and of the Lausanne University Hospital (CHUV) as Associate Professor ad personam.  Dr Thiran's current scientific interests include Computational medical imaging: acquisition, reconstruction and analysis of imaging data, with emphasis on regularized linear inverse problems (compressed sensing, convex optimization). Applications to medical imaging: diffusion MRI, ultrasound imaging, inverse planning in radiotherapy, etc.Computer vision & machine learning: image and video analysis, with application to facial expression recognition, eye tracking, lip reading, industrial inspection, medical image analysis, etc.
Heinz Hügli
Heinz Hügli est professeur honoraire à l'Ecole Polytechnique Federale de Lausanne (EPFL). Il a été directeur de recherches et professeur associé à l'Institut de Microtechnique de l'Université de Neuchâtel, Suisse, où il était chargé d'un enseignement et dirigeait le Laboratoire de Reconnaissance des Formes. De 1988 à 2008, ce laboratoire a conduit des recherches dans les domaines de la vision par ordinateur, avec un accent particulier sur la vision précoce, l'inspection industrielle, la modélisation et la reconnaissance d'objets 3D. Heinz Hügli est ingénieur diplômé de l'Ecole Polytechnique Fédérale de Zurich (EPFZ) où il obtint aussi son titre de docteur en sciences techniques. Il a travaillé cinq ans dans le cadre du groupe de traitement des images à l'EPFZ et deux ans avec le Medical Imaging Science Group, University of Southern California. En 1982, il rejoint l'Université de Neuchâtel, Suisse, où il conduisit des recherches dans le domaine du traitement de la parole avant de créer le Laboratoire de reconnaissance des formes (PARLAB). Il a enseigné à l'Université de Neuchâtel, l'Université de Berne et l'EPFL. Auteur de plus de 150 publications scientifiques, il a présidé des conférences internationales, a été membre de plusieurs socités scientifiques et a participé aux comités de programmes de nombreuses conférences.

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.