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.
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
Athanasios NenesTeaching & PhD PhD Students Berkay Dönmez, Ernest Abboud Past EPFL PhD Students Paraskevi Georgakaki, Lucile Ricard Courses Atmospheric processes: from cloud to global scales ENV-407 The main objective is to present important atmospheric processes from the local to global scales. The course will start with cloud processes, continue to synoptic phenomena like extratropical cyclones and fronts, to finally cover numerical modeling at the regional and global scales. Introduction to environme
Mats Julius StensrudTeaching & PhD PhD Students Ignacio Gonzalez Perez, Gellért Géza Perényi, Lorenzo Gasparollo, Julien David Laurendeau Past EPFL PhD Students Matias Janvin, Amit Sawant Courses Causal thinking MATH-352 This course will give a unified presentation of modern methods for causal inference. We focus on concepts, and we will present examples and ideas from various scientific disciplines, including medicine, computer science, engineering, economics and epidemiology. Probability and statistics (
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
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.
Francesca RodinoExpertise
Electrochemical BiosensorsSensors and Biosensors interfaces | front-end electronicsBiomedical circuits and systems
Francesca Rodino received the B.Sc. and M.Sc. degrees in Biomedical Engineering from the Politecnico di Torino, Turin, Italy, in 2019 and 2022, respectively. She developed her Master's project in the field of cortical neuroprosthesis devices for artificial vision in collaboration with the Integrated Circuits Laboratory (ICLAB) at école Polytechnique Fédérale de Lausanne (EPFL) in Swit
Du WenEducation PhD | Doctor of Philosophy, Mechanical Engineering 2020 – 2023 The University of Tokyo MEng | Master of Engineering, Power Engineering and Engineering Thermophysics 2016 – 2019 Xi’an Jiaotong University Bsc | Bachelor of Engineering 2012 – 2016 Xi’an Jiaotong University
Show more