Olga FinkTeaching & PhD PhD Students Han Sun, Leandro Von Krannichfeldt, Keivan Faghih Niresi, Zepeng Zhang, Vinay Sharma, Chenghao Xu, Raffael Pascal Theiler, Kevin Antonio Steiner, Sergei Garmaev, Amaury Wei Past EPFL PhD Students Ismail Nejjar, Mengjie Zhao Courses Data Science for infrastructure condition monitoring CIVIL-332 The course will cover the relevant steps of data-driven infrastructure condition monitoring, starting from data acquisition, going through the steps pre-processing of real
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)
Teaching & PhD Past EPFL PhD Students as codirector Pierpaolo Ranieri Courses Scanning and Analytical Transmission Electron Microscopy MSE-735 This intensive course discusses advanced TEM techniques such as: scanning TEM; analytical TEM using EELS and EDX; aberration corrected imaging; and image s
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 PiazzaTeaching & PhD PhD Students Claire Valentine Blaga, Matilde Cantele, Julia Sarah Marhic Past EPFL PhD Students as codirector Michele Zendrini Courses Functional properties of materials MSE-210 The main objective of this course is to present the concepts allowing the understanding of the fundamental principles that enable to predict the properties of the materials. The goal is that with these concepts, one will be able to realize material design and/or to understand novel materials.
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
Teaching & PhD Courses Scanning and Analytical Transmission Electron Microscopy MSE-735 This intensive course discusses advanced TEM techniques such as: scanning TEM; analytical TEM using EELS and EDX; aberration corrected imaging; and image simulation. It is intended for researchers who have taken the introductory TEM course MSE-637 or who have a good background in conventional TEM.
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 SchneiderTeaching & PhD Courses Integrative structural biology for Life sciences BIO-643 Hands-on course in Biomolecular Integrative Structural Biology by SV experts in the field of X-ray crystallography, cryo-Electron Microscopy, Bio-NMR and protein modeling tools. No previous knowledge in Structural Biology or Bioinformatics is required.
Elise Rose ErayTeaching & PhD Courses Practical - Antanasijevic Lab BIO-614 The students will learn: 1) how to handle viral protein antigens and antibody samples 2) how to assemble and purify immune complexes using liquid chromatography 3) how to image them on an electron microscope
