Barbara GalimbertiExpertise
Archival science, collections management, and information sciences applied to architectural archives and to heritage and research collections, within the Archives of Modern Construction (ACM) of the École polytechnique fédérale de Lausanne.Standardized archival description, metadata structuring and governance, dissemination of finding aids, and development of digital infrastructures for long-term preservation and access (Morphé / AtoM + Archivematica ; MorphéPlus).Intellectual and physical process
Karen ScrivenerDe nationalité anglaise, Karen Scrivener est née en 1958. Au cours de sa carrière, ses travaux et sa recherche traitaient des domaines suivants: Identification du développement microstucturale pendant l'hydratation du ciment. Elaboration d'une approche multitechnique pour étudier la microstucture des ciments et bétons, avec accent sur la quantification par analyse des images d'électrons retrodiffusés. Caractérisation de l'auréole de transition de la pâte de ciment autour des granulats. Compréhension des processus de dégardation des bétons, en particulier le gonflement lié à la formation de l'éttringite retardée dans les bétons étuvés.
Marco PicassoExpertise
Computational Science and Engineering
Mission
I am teaching analysis and numerical analysis for engineers and mathematicians at bachelor and master levels.My research pertains to the numerical simulation of complex physical systems with partial differential equations.Here is some bibliometry: Google Scholar, Research Gate, Orcid, here is my most recent CV. Ongoing research projects: - Numerical simulation of aluminium electrolysis, collaboration with RioTinto LRF lab, Ycoorsystems SA and Jacques
Samuel DubuisAfter mathematics studies at EPFL, I go on with a PhD thesis under the supervision of Prof. Marco Picasso. Interested in teaching, I turn to the preparatory year of EPFL (CMS) where I worked since 2020.Centers of interests I like to work in classroom with students, in particular to guide them through elementary mathematics contents, that are the basis of engineering and experimental sciences.I also work with Prof. Picasso and his PhD and intern students in the fields of scientific computing and numerical a
Mackenzie MathisCenter for NeuroprostheticsEPFL ELLIS Unit Faculty MemberCenter for Intelligent Systems
Alexander MathisAlexander studied pure mathematics with a minor in logic and theory of science at the Ludwig Maximilians University in Munich. For his PhD also at LMU, he worked on optimal coding approaches to elucidate the properties of grid cells. As a postdoctoral fellow with Prof. Venkatesh N. Murthy at Harvard University and Prof. Matthias Bethge at Tuebingen AI, he decided to study olfactory behaviors such as odor-guided navigation, social behaviors and the cocktail party problem in mice. During this time, he increasingly got interested sensorimotor behaviors beyond olfaction and started working on proprioception, motor adaption, as well as computer vision tools for measuring animal behavior.
In his group, he is interested in elucidating how the brain gives rise to adaptive behavior. One of the major goals is to synthesize large datasets into computationally useful information. For those purposes, he develops algorithms and systems to analyze animal behavior (e.g. DeepLabCut), neural data, as well as creates experimentally testable computational models.
Pascal FuaPascal Fua received an engineering degree from Ecole Polytechnique, Paris, in 1984 and the Ph.D. degree in Computer Science from the University of Orsay in 1989. He then worked at SRI International and INRIA Sophia-Antipolis as a Computer Scientist. He joined EPFL in 1996 where he is now a Professor in the School of Computer and Communication Science and heads the Computer Vision Laboratory. His research interests include shape modeling and motion recovery from images, analysis of microscopy images, and Augmented Reality. His research interests include shape modeling and motion recovery from images, analysis of microscopy images, and machine learning. He has (co)authored over 300 publications in refereed journals and conferences. He is an IEEE Fellow and has been an Associate Editor of IEEE journal Transactions for Pattern Analysis and Machine Intelligence. He often serves as program committee member, area chair, and program chair of major vision conferences and has cofounded three spinoff companies (Pix4D, PlayfulVision, and NeuralConcept).
Nicolas GrandjeanNicolas Grandjean received a PhD degree in physics from the University ofNice Sophia Antipolis in 1994 and shortly thereafter joined the French National Center for Scientific Research (CNRS) as a permanent staff member. In 2004, he was appointed tenure-track assistant professor at the École polytechnique fédérale de Lausanne (EPFL) where he created the Laboratory for advanced semiconductors for photonics and electronics. He was promoted to full professor in 2009. He was the director of the Institute of Condensed Matter Physics from 2012 to 2016 and then moved to the University of California at Santa Barbara where he spent 6 months as a visiting professor. Since 2018, he is the head of the School of Physics at the EPFL. He was awarded the Sandoz Family Foundation Grant for Academic Promotion, received the “Nakamura Lecturer” Award in 2010, the "Quantum Devices Award” at the 2017 Compound Semiconductor Week, and “2016 best teacher” award from the EPFL Physics School. His research interests are focused on the physics of nanostructures and III-V nitride semiconductor quantum photonics.
Francesco VarratoExpertise
Simulation and theory of coarse grained models of soft matter. Studies on colloidal gels, polymer melts, supercooled liquids and glassy systems. Research on physical fractals and dynamically arrested amorphous structures.
Expertise
Simulation and theory of coarse grained models of soft matter. Studies on colloidal gels, polymer melts, supercooled liquids and glassy systems. Research on physical fractals and dynamically arrested amorphous structures.
Teaching & PhD Courses Hands-on with Research
Chiara GabellaTeaching & PhD Courses Hands-on with Research Data Management in Chemistry ChE-601 PhD students in Chemistry will learn hands-on Research Data Management (RDM) skills transferable to their research practices. They willcontextualize their research into RDM best practices (day 1), discover appropriate tools (day 2) and work on a project (day 3) for the courseaccreditation
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