Simon GuilloudExpertise
My main domains of research are proof assistants and algorithms for logic-related problems.I also have interests in various areas of computer science and mathematics and their applicability in proof systems such as probabilistic proofs, type theory, quantum computing and more.
Expertise
My main domains of research are proof assistants and algorithms for logic-related problems.I also have interests in various areas of computer science and mathematics and their applicability in proof systems such as
Bruno Emanuel Ferreira De Sousa CorreiaThroughout my PhD and postdoctoral studies I was trained in world-renowned laboratories and institutions in the United States of America (University of Washington and The Scripps Research Institute). Very early in my scientific career I found out my fascination about protein structure and function. My PhD studies evolved in the direction of immunogen design and vaccine engineering which sparked my interest in the many needs and opportunities in vaccinology and translational research. My efforts resulted in an enlightening piece of work where for the first time, computationally designed immunogens elicited potent neutralizing antibodies. During my postdoctoral studies I joined a chemical biology laboratory at the Scripps Research Institute. In this stage I developed novel chemoproteomics methods for the identification of protein-small molecule interaction sites in complex proteomes. In March 2015, I joined the École Polytechnique Fédérale de Lausanne (EPFL) – Switzerland as a tenure track assistant professor. The focus of my research group is to develop computational tools for protein design with particular emphasis in applying these strategies to immunoengineering (e.g. vaccine and cancer immunotherapy). The activities in my laboratory focus on computational design methods development and experimental characterization of the designed proteins. Our laboratory has been awarded with 2 prestigious research grants from the European Research Council. Lastly, I have been awarded the prize for best teacher of Life sciences in 2019.
Elison de Nazareth MatioliTeaching & PhD PhD Students Hongkeng Zhu, Yuan Zong, Utku Agtas, Ibrahim Osama Elhagali, Mohammad Rezaei, Zheng Hao, Amirhossein Esteghamat, Ivan Krsic, Luca Mazzone, Önder Soydal, Francesco Marcantoni, Hakan Cankat Gür Past EPFL PhD Students Jun Ma, Giovanni Santoruvo, Minghua Zhu, Riyaz Mohammed Abdul, Reza Soleiman Zadeh Ardebili, Armin Jafari, Catherine Erine, Taifang Wang, Nirmana Perera, Remco Franciscus Peter van Erp, Luca Nela, Mohammad Samizadeh Nikoo, Alessandro Floriduz Past EPFL PhD Students a
Sara BonellaExpertise
Simulation and modelling of condensed phase systems, quantum and classical dynamics and statistical mechanics, adiabatic dynamics for classical polarizable models and first principles simulations, classical charge transport for systems in external magnetic fields.
Expertise
Simulation and modelling of condensed phase systems, quantum and classical dynamics and statistical mechanics, adiabatic dynamics for classical polarizable models and first principles simulations, classical charge transport for
Bryan Alexander FordLinks
DEDIS lab home pagePersonal home page
Curriculum vitae https://bford.info/cv.pdf
Teaching & PhD PhD Students Shailesh Mishra Past EPFL PhD Students Eleftherios Kokoris Kogias, Kirill Nikitin, Cristina Basescu, Enis Ceyhun Alp, Simone Colombo, Pasindu Nivanthaka Tennage, Louis-Henri Manuel Jakob Merino Past EPFL PhD Students as codirector David Froelicher, Ludovic Barman, Georgia Fragkouli Courses Decentralized systems engineering CS-438 A decentralized system is one that works when n Maria BrbicMaria Brbic is an assistant professor in computer science at EPFL. Prior to joining EPFL, Maria was a postdoctoral researcher in Computer Science at Stanford University working with Jure Leskovec. She received her PhD degree from University of Zagreb in 2019, while also researching at Stanford University and University of Tokyo. Her research was awarded with the Fulbright Scholarship, L’Oreal UNESCO for Women in Science Scholarship, Branimir Jernej award for outstanding publication in biology and biomedicine, and Josip Loncar Silver Plaque award for the best doctoral dissertation. She has been named a Rising Star in EECS by MIT in 2021. Her research is focused on developing new machine learning methods and applying her methods to advance biomedical research.
André ChatelExpertise
Micro and NanotechnologiesMicroelectronicsSolid State PhysicsQuantum Physics
Born in Aosta (Italy) in 1996, I obtained a 110L/110 Bachelor degree in Physical Engineering from Politecnico di Torino in 2018. I then followed a Master joined program in Nanotechnologies for ICTs, shared between PoliTO, INPG-Phelma and EPFL, getting graduated in 2020, with a 110L/110 score.In summer 2019, I joined Dr. Sallese group at EPFL-EDLAB to carry out an internship in modeling and simulation of radiation-induced
Cécile HardebolleCurrent work
Responsible information systems (https://go.epfl.ch/digitalethics), ethical skills Jupyter notebooks for education (https://go.epfl.ch/notebooks), digital skills, computational thinking Transversal/professional skillsEngineering design skillsFlipped classrooms Project-based learning
Education PhD | Computer Science 2006 – 2008 Université Paris-Sud XI, France Directed by Prof. Guy Vidal-Naquet MSc | Electrical Engineering, major in Computer and Inf Johanni Michael BreaTeaching & PhD PhD Students Aude Maier, Lucas Louis Gruaz, Flavio Martinelli Courses Artificial intelligence and society HUM-286 This course integrates social sciences and humanities with engineering sciences, and introduces students to the social, technical and political issues surrounding artificial intelligence. Biological data science II : machine learning BIO-322 Students understand basic concepts and methods of machine learning. They can describe them in mathematical
Maude GirardinTeaching & PhD Courses Analysis A (for MAN) PREPA-031(a) This course offers the basic tools in calculus and in solving of equations and inequations on real and complex numbers.The course explores the study of elementary fonctions and is a basis for the calculus course. Analysis II (for CMS) PREPA-005(a) This class focus on the studies of special functions : trigonometric, logarithmic and exponential functions. Linear Algebra (for CMS) PREPA-002 the goal is to
Isabella Di LenardoPh.D. in Theories and Art History. Isabella di Lenardo is senior scientist in Digital Humanities and Urban History. Her research activity is focused on digital tools and methods applied to Urban History. She is an expert in ancient cartography, city representations, cadastral sources interpreted through digital modeling, extraction and analysis systems.She's also interested in network analysis questioning the production and circulation of artistic and architectural knowledge in Europe XVIth – XVIIIth centuries in particular on North-South relationships and influences. The development of collaboration projects with European institutions and the activity carried out on various initiatives supported by the European Commission have allowed her to acquire specialism in the field of science applied to heritage, developing in particular specific skills for the enhancement of Cultural Heritage through digital tools. She leads projects in collaboration with Bibliothèque national de France (Paris), Institut National d’Histoire de l’Art (Paris), Ecole nationale des chartes (Paris), Université Paris I Panthéon-Sorbonne, Centre Allemand d’Histoire de l’Art (Paris), Musée du Louvre, Archives Nationales de Paris, Bibliothèque Historique de la Ville de Paris, Réunion des Musées Nationaux. She supervised all the urban modeling simulations for the Venice Time Machine project and acted as content curator for all the exhibitions (Venice Biennale, Grand Palais-Paris, Datasquare - ArtLab-Lausanne, Museo Correr-Venice). She was Head of “Replica” project : digitizing 1 million photos of artworks in the Fondazione Giorgio Cini (Venice) and visual patterns extraction through a search engine for visual similarities. She has a Ph.D in Art History and also studied Archaeology and Urban Studies. She has published essays and articles about Venetian Art and Urban History and participated in many Art exhibitions in European museums. She coordinated summer schools and workshops about Digital Tools for Art History and Urban History. She attended conferences on digital methods for History in universities and patrimonial institutions.
Yifan HuExpertise
Optimization, Operations Research, Reinforcement Learning
I am a Postdoc with Prof. Daniel Kuhn from EPFL and Prof. Andreas Krause from ETH Zurich. Prior to that, I got my PhD in Operations Research from University of Illinois at Urbana-Champaign, advised by Prof. Xin Chen and Prof. Niao He. My research interest lies in data-driven decision-making with problems arising from optimization, operations research, and statistics. See Research for research directions and Publication for papers.
