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
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.
Amaury Pierre Jiezhi WeiExpertise
Deep Learning, Computer Vision, Physics Informed Machine Learning, Graph Neural Networks
Amaury obtained his Master's degree in Robotics from the Federal Institute of Technology in Lausanne (EPFL) in 2021.Before joining IMOS, he worked for multiple years at Logitech Europe S.A. as a Software Engineer in the field of Augmented and Virtual Reality. He researched 6DoF tracking solutions for handheld devices, developed the firmware and designed the testing strategy for the MR Stylus MX Ink.During his
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.
David Richard HarveyExpertise
CosmologyDark MatterGalaxy ClustersStrong Gravitational LensingWeak Gravitational Lensing
I am an observational and theoretical astrophysicist at EPFL. My main area of research is dark matter and trying to understand its properties and dynamics. I love to use deep learning in my work and understand how fondation models and generative AI can help us understand the Universe. I am a member of Euclid and ARRAKIHS and the lead of the self interacting dark matter Key Project in Euclid. Outside of my r
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
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.
Loris Di NataleExpertise
(Deep) Machine Learning, (Deep) Reinforcement Learning, Building Control
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