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
Leonard Paul Arthur HardimanEnseignement et PhD Cours Analyse I (pour CMS-3) PREPA-003(b) Ce cours du premier semestre vise à établir les bases du calcul différentiel. ICS (pour CMS) PREPA-025 Ce cours présente les fondements de la programmation Python avec une introduction à la pensée algorithmique à travers des algorithmes fondamentaux. Informatique et calcul scientifique (pour MAN) PREPA-094 Après une introduction à la programmation Python et à l'algorithmique, des méthodes numériques
Paul Robert GuhennecMes recherches portent sur l'utilisation de méthodes informatiques pour l'histoire de l'architecture et leurs implications épistémologiques. Je suis actuellement chercheur post-doctoral au Digital Humanities Laboratory de l'EPFL, où j'ai récemment terminé ma thèse de doctorat sur l'histoire urbaine et architecturale de Venise, intitulée «The Skin of Venice: A Computational Approach to the City's Urban Structure».
Sanggyu ChongSanggyu "Raymond" Chong obtained his BS, MS and PhD degrees in Chemical and Biomolecular Engineering from Korea Advanced Institute of Science and Technology (KAIST), where he primarily focused on the computational design of metal-organic frameworks for applications ranging from gas storage to functional electronics. In March 2022, Sanggyu joined COSMO as a postdoctoral researcher, and he is currently investigating the robustness of local and/or component-wise predictions made by atomistic machine learning m
Guillaume AnciauxEnseignement et PhD Doctorant·es actuel·les Parissasadat Alavi, Thibault Ghesquière-Diérickx A co-dirigé les thèses EPFL de Srinivasa Babu Ramisetti, Jaehyun Cho, Lucas Frérot, Mohit Pundir, Manon Eugénie Voisin--Leprince Cours Modélisation numérique des solides et structures CIVIL-321 La modélisation numérique des solides est abordée à travers la méthode des éléments finis. Les aspects purement analytiques sont d'abord présentés, puis les moyens d'interpolation, d'intégration et de résolu
Henry MarkramEnseignement et PhD Doctorant·es actuel·les Davide Bella A dirigé les thèses EPFL de Tania Rinaldi, Jean-Vincent Le Bé, Michele Pignatelli, Thomas Berger, Luca Gambazzi, Rodrigo de Campos Perin, Imad Riachi, Muhammad Asif Jan, Rajnish Ranjan, Srikanth Ramaswamy, Georges Khazen, Vincent Delattre, Mônica Favre, Shruti Muralidhar, Michael Reimann, Jean Pierre Ghobril, Renaud Luc Richardet, Marwan Abdellah, Willem Wybo, Csaba Erö, Lida Kanari, Giuseppe Chindemi, Berat Denizdurduran, Max Nolte, Taylor Howard N
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•
Patrick Daniel BarthProfessor Patrick Barth is Associate Professor at EPFL and Adjunct Associate Professor at Baylor College of Medicine, Houston, TX, USA. He received training in Physics, Chemistry and Biology (University of Paris, ENS) in France and performed his PhD at the Commissiariat a l'Energie Atomique in Saclay, France on structure/function studies of membrane proteins (photosystem I) using biochemical and biophysical experimental techniques. He carried out postdoctoral studies at University of California at Berkeley with Tom Alber on computational development for calculating protein electrostatics and designing de novo selective peptide inhibitors of cellular protein interactions. He then went to the University of Washington as a postdoctoral fellow and instructor in David Baker's laboratory to develop computational techniques in the software Rosetta for predicting and designing membrane protein structures. He started his independent career and received tenure at Baylor College of Medicine. He will continue at EPFL to marry computation and experiment for understanding the molecular determinants of signal transduction, as well as modeling and designing membrane proteins with novel functions for various synthetic biology and therapeutic applications.
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.
Berend SmitEnseignement et PhD Doctorant·es actuel·les Anastasia Blokhina, Raluca-Ana Kessler, Seyed Amirmohammad Elahi, Juliette Veronique Schleicher, Yutao Li, Xin Jin, Sara Bassetta, Beatriz Bueno Mouriño A dirigé les thèses EPFL de Samantha Lynn Anderson, Daniele Ongari, Andrzej Gladysiak, Seyedmohamad Moosavi, Arunraj Chidambaram, Bardiya Valizadeh, Stavroula Kampouri, Fatmah Ebrahim, Fatma Pelin Uran, Andres Adolfo Ortega Guerrero, Kevin Maik Jablonka, Elias Moubarak, Sauradeep Majumdar, Miriam Jasmin Pougin,
Luciano Andres AbriataEnseignement et PhD Cours Basic and advanced NMR - Level 1 A (EPFL) CH-601(x) Basic and advanced NMR - Level 2 (EPFL) CH-703 The goal is to give a sound theoretical and practical foundation in NMR for various applications in research. PhD students and post-docs who have followed the course successfully should be able to perform modern multi-dimensional NMR experiments independently. Integrative structural biology for Life sciences BIO-643 Recombinant protei
Sofia Charlotta OlhedeSofia Olhede is a professor of Statistics at EPFL in Switzerland. She joined UCL prior to this in 2007, before which she was a senior lecturer of statistics (associate professor) at Imperial College London (2006-2007), a lecturer of statistics (assistant professor) (2002-2006), where she also completed her PhD in 2003 and MSci in 2000. She has held three research fellowships while at UCL: UK Engineering and Physical Sciences Springboard fellowship as well as a five-year Leadership fellowship, and now holds a European Research Council Consolidator fellowship. Sofia has contributed to the study of stochastic processes; time series, random fields and networks. Sofia was part of the multi-institutional team that set up the UK national data science institute, the Alan Turing Institute. She organised and served as chair of the science committee that developed the initial 500 000 pounds scientific programme of the institute; peer-reviewing over 100 workshop proposals and hosting over 30. She also chaired the first recruitment wave of the institute hiring 13 data scientists as a multi-university recruitment drive. Sofia was a member of the Royal Society and British Academy Data Governance Working Group, and the Royal Society working group on machine learning. Most recently she was one of 3 commissioners on a law society commission on the usage of algorithms in the justice system.
Mats Julius StensrudEnseignement et PhD Doctorant·es actuel·les Ignacio Gonzalez Perez, Gellért Géza Perényi, Lorenzo Gasparollo, Julien David Laurendeau A dirigé les thèses EPFL de Matias Janvin, Amit Sawant Cours Causal thinking MATH-352 Ce cours donnera une présentation unifiée des méthodes modernes d'inférence causale. Nous nous concentrons sur les concepts, et nous présenterons des exemples et des idées provenant de diverses disciplines scientifiques, notamment la médecine, l'informatique, l'ingénierie,
Hervé BourlardEnseignement et PhD A dirigé les thèses EPFL de Astrid Hagen, Katrin Weber, Todd Stephenson, Jitendra Ajmera, Shajith Ikbal, Mathew Magimai Doss, Mohamed Faouzi Benzeghiba, Mark Barnard, Yann Rodriguez, Hemant Misra, Christos Dimitrakakis, Guillaume Lathoud, Alexei Pozdnoukhov, Agnès Just, Mikaela Keller, Norman Hoon Thian Poh, Dong Zhang, Florent Monay Michaud, Pedro Manuel Da Silva Quelhas, Kevin Smith, Silèye Oumar Ba, Bertrand Mesot, Hamed Ketabdar, David Grangier, Guillermo Aradilla, Jean-François Paie
Viktor KuncakViktor Kunčak joined EPFL in 2007, after receiving a PhD degree from MIT. Since then has been leading the Laboratory for Automated Reasoning and Analysis and supervised at least 12 completed PhD theses. His works on languages, algorithms and systems for verification and automated reasoning. He served as an initiator and one of the coordinators of a European network (COST action) in the area of automated reasoning, verification, and synthesis. In 2012 he received a 5-year single-investigator European Research Council (ERC) grant of 1.5M EUR. His invited talks include those at Lambda Days, Scala Days, NFM, LOPSTR, SYNT, ICALP, CSL, RV, VMCAI, and SMT. A paper on test generation he co-authored received an ACM SIGSOFT distinguished paper award at ICSE. A PLDI paper he co-authored was published in the Communications of the ACM as a Research Highlight article. His Google Scholar profile reports an over-approximate H-index of 38. He was an associate editor of ACM Transactions on Programming Languages and Systems (TOPLAS) and served as a co-chair of conferences on Computer-Aided Verification (CAV), Formal Methods in Computer Aided Design (FMCAD), Workshop on Synthesis (SYNT), and Verification, Model Checking, and Abstract Interpretation (VMCAI). At EPFL he teaches courses on functional and parallel programming, compilers, and verification. He has co-taught the MOOC "Parallel Programming" that was visited by over 100'000 learners and completed by thousands of students from all over the world.
Maud EhrmannMaud Ehrmann is a research scientist at EPFL’s Digital Humanities Laboratory lead by Prof.
Frédéric Kaplan
. She holds a PhD in Computational Linguistics from the Paris Diderot Universtiy (Paris 7) and has been engaged in a large number of scientific projects centred on information extraction and text analysis, both for present-time and historical documents. Her main research interests span Natural Language Processing and Digital Humanities and include, among others, historical text annotation, historical data processing and representation, named entity recognition, and multilingual linguistic resources creation.
Her current work at the DHLAB focuses on
‘impresso - Media Monitoring of the Past’
, a SNF sinergia project she initiated with
Marten Düring
(
C2DH
) and
Simon Clematide
(
ICL
) and which aims at enabling critical analysis of historical newspapers. In addition to the overall project management, her contributions to this project include system design and data management, annotation and benchmarking and named entity processing. Besides, she participates to the activities of the
Venice Time Machine
, working particularly on information extraction and knowledge representation tasks. Previously, she worked on the
Garzoni
project where she supervised and contributed to the development of a web-based transcription and annotation interface - in collaboration with Orlin Topalov, and built a linked data-based historical knowledge base. She also contributed to the
Le Temps Digital Archives project
.
Prior to joining the DHLAB, she worked at the
Linguistics Computing Laboratory
at the Sapienza University of Rome with Roberto Navigli, where she worked on the
BabelNet
resource - a very large multilingual encyclopaedic dictionary and semantic network - and contributed to the
LIDER
project. Before that, she has been working for four years at the European Commission’s Joint Research Centre in Ispra, Italy, as member of the OPTIMA unit (now
Text and Data mining
unit), which develops innovative and application-oriented solutions for retrieving and extracting information from the Internet with a focus on high multilinguality. Together with Erik van der Goot,
Ralf Steinberger
, Hristo Tanev, Leo della Rocca and many others, she contributed to the development of the
Europe Media Monitor
(EMM). Prior, she worked at the Xerox Europe Research Centre in Grenoble, France (now
Naver Labs Europe
) in the Parsing & Semantics group led by Frédérique Segond, first as PhD candidate supported through a CIFRE grant under the supervision of
Caroline Brun
and
Bernard Victorri
, then as a post-doctoral researcher. There her research focused mainly on the automatic processing and fine-grained analysis of entities of interest, specifically named entities and temporal expressions.
