Olga FinkEnseignement et PhD Doctorant·es actuel·les Han Sun, Leandro Von Krannichfeldt, Keivan Faghih Niresi, Zepeng Zhang, Vinay Sharma, Chenghao Xu, Raffael Pascal Theiler, Kevin Antonio Steiner, Sergei Garmaev, Amaury Wei A dirigé les thèses EPFL de Ismail Nejjar, Mengjie Zhao Cours Data Science for infrastructure condition monitoring CIVIL-332 Le cours couvrira les étapes pertinentes de la surveillance de l'état des infrastructures basée sur les données: l'acquisition des données, en passant p
Lenka ZdeborováLenka Zdeborová is a Professor of Physics and of Computer Science in École Polytechnique Fédérale de Lausanne where she leads the Statistical Physics of Computation Laboratory. She received a PhD in physics from University Paris-Sud and from Charles University in Prague in 2008. She spent two years in the Los Alamos National Laboratory as the Director's Postdoctoral Fellow. Between 2010 and 2020 she was a researcher at CNRS working in the Institute of Theoretical Physics in CEA Saclay, France. In 2014, she was awarded the CNRS bronze medal, in 2016 Philippe Meyer prize in theoretical physics and an ERC Starting Grant, in 2018 the Irène Joliot-Curie prize, in 2021 the Gibbs lectureship of AMS. She is an editorial board member for Journal of Physics A, Physical Review E, Physical Review X, SIMODS, Machine Learning: Science and Technology, and Information and Inference. Lenka's expertise is in applications of concepts from statistical physics, such as advanced mean field methods, replica method and related message-passing algorithms, to problems in machine learning, signal processing, inference and optimization. She enjoys erasing the boundaries between theoretical physics, mathematics and computer science.
Victor Carle Adrien BoureauExpertise
Aberration-corrected TEM and STEMQuantative microscopyElectron diffractionStrain mapping (GPA, precession 4D-STEM)Electric and magnetic field mapping (electron holography, DPC, 4D-STEM)
Enseignement et PhD A co-dirigé les thèses EPFL de Pierpaolo Ranieri Cours Scanning and Analytical Transmission Electron Microscopy MSE-735 Transmission electron microscopy and diffraction (a) MSE-637(a) This course is for potential new users of transmission electron microscopes for
Anne-Florence Raphaëlle BitbolI was trained in physics, and always had a strong interest in biology. I am broadly interested in understanding biological phenomena in a quantitative way, through physical concepts and mathematical and computational tools. I investigate the relative impacts of optimization and historical contingency in biological evolution, both at the scale of protein sequences and at the scale of microbial populations.Here is my research group website.Curriculum vitae Here is my complete CV. Professional experience:Since
Martin SchrimpfExpertise
NeuroAI, computational neuroscience, computer vision, natural language processing, human alignment, startups [CV]
Mission
Modeling the brain: Martin's research focuses on a computational understanding of the neural mechanisms underlying natural intelligence in vision and language. To achieve this goal, he bridges Deep Learning, Neuroscience, and Cognitive Science, building artificial neural network models that match the brain’s neural representations in their internal processing and are aligned to
Valerio PiazzaEnseignement et PhD Doctorant·es actuel·les Claire Valentine Blaga, Matilde Cantele, Julia Sarah Marhic A co-dirigé les thèses EPFL de Michele Zendrini Cours Propriétés fonctionnelles des matériaux MSE-210 Ce cours a comme objectif de présenter les concepts nécessaires à la compréhension des principes fondamentaux qui permettent de prédire les propriétés d'un matériau. Ces concepts vous permettront de réaliser du "material design" et de comprendre même des nouveaux matériaux pas encore étu
Milad SabzehparvarExpertise
Scanning Electrochemical MicroscopyPlasmonic PhotocatalysisMaterial ScienceOpen MSc positions (2023-2024):(1) Design and Fabrication of a Scanning Electrochemical Microscope (SECM) for Photo-Electrochemical Imaging of Nanostructures, (2) Data and Image Analysis of Scanning Electrochemical Microscopy (SECM)
Expertise
Scanning Electrochemical MicroscopyPlasmonic PhotocatalysisMaterial ScienceOpen MSc positions (2023-2024):(1) Design and Fabrication of a Scanning Electrochemical Microscope (SECM) for
David Fernando Reyes VasquezExpertise
Electron energy loss spectroscopy (EELS)Aberration-corrected TEM and STEM
Enseignement et PhD Cours Scanning and Analytical Transmission Electron Microscopy MSE-735
Ghassan ShahinExpertise
I am a geomechanics researcher with interests in the mechanical behavior of the Earth's materials at conditions pertaining to the shallow Earth and upper mantle. In my studies, I employ laboratory geomechanics backed by x-ray methods, advanced constitutive modeling, and material theories to study failure patterns across scales spanning from the grain-scale up to the field-scale.
Expertise
I am a geomechanics researcher with interests in the mechanical behavior of the Earth's materials at condition
Andrew James SontaExpertise
Human-building interaction, building energy, occupant behavior, sustainable design and planning, walkability, network analysis, machine learning, urban informatics, social systems.
Andrew Sonta is a tenure track assistant professor of sustainable civil engineering at EPFL. He directs the ETHOS Lab: Engineering and Technology for Human Oriented Sustainability. ETHOS is an interdisciplinary research group focused on using data-driven and computational tools to create interventions in the built envir
Mackenzie MathisCenter for NeuroprostheticsEPFL ELLIS Unit Faculty MemberCenter for Intelligent Systems
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•
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.
Jonathan SchneiderEnseignement et PhD Cours Integrative structural biology for Life sciences BIO-643
Elise Rose ErayEnseignement et PhD Cours Practical - Antanasijevic Lab BIO-614
