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.
Zoë HolmesEnseignement et PhD Doctorant·es actuel·les Ricard Puig, Sacha Lerch, Reyhaneh Aghaei Saem, Shao Hen Chiew, Weijie Xiong, Marc Sanz Drudis, Mehrad Sahebi, Manuel Rudolph Cours Quantum information theory PHYS-550 Après avoir revu les bases de la théorie quantique du point de vue de la théorie de l'information, nous couvrirons des sujets plus avancés en théorie de l'information quantique tels que les mesures de l'information quantique et la compréhension des états, canaux et mesures quantiqu
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
Manuel Sebastian RudolphExpertise
Computational quantum physicsQuantum algorithmsQuantum machine learningGenerative modeling
Manuel is a PhD Candidate at EPFL in the group of Prof. Zoë Holmes, where he focuses on the numerical simulation of quantum computers. Together with his collaborators, he studies which properties make quantum circuits easy or hard to simulate classically, and how efficient classical simulability is connected to the barren plateau phenomenon. Manuel develops high-performance quantum simulation software and is
Virginia CarnevaliExpertise
Theoretical condensed matter physics: theory and simulations of structural, electronic, magnetic and optical properties (Quantum ESPRESSO), ab-initio molecular dynamics (CP2K), and Kinetic Monte Carlo codes; automate Quantum ESPRESSO workflows and high-throughput calculations (AFLOWÏ€); generation of tight-binding hamiltonians, transport properties, and data analysis (PAOFLOW).Materials for photovoltaic: Pb- and Sn-based organic perovskites; investigation and improvement of the HTL-ETL interaction
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•
Ricard Puig I VallsExpertise
I'm interested on Variational Quantum Algorithms, Quantum Simulation and Quantum Metrology and Sensing. Overall in general I love studying how we can exploit quantum resources to surpass the classical limits.
Expertise
I'm interested on Variational Quantum Algorithms, Quantum Simulation and Quantum Metrology and Sensing. Overall in general I love studying how we can exploit quantum resources to surpass the classical limits.
I obtained my BSc in Physics in 2022 from the Autonomous University of Bar
Charlotte Cäcilie Gertrud BunneCharlotte Bunne is an assistant professor at EPFL in the School of Computer and Communication Sciences (IC) and School of Life Sciences (SV). She is part of the Swiss Institute for Experimental Cancer Research (ISREC) and the EPFL AI Center. Before, she was a PostDoc at Genentech and Stanford working with Aviv Regev and Jure Leskovec and completed a PhD in Computer Science at ETH Zurich working with Andreas Krause and Marco Cuturi. During her graduate studies, she was a visiting researcher at the Broad Inst
Gregor JotzuEnseignement et PhD Doctorant·es actuel·les Malo Pierre Yves Herve, Louis Gobber, Chiara Missaglia, Kewei Zhou, Fares Hasan Cours Probability and statistics for materials science MSE-213 Établit les concepts de l'analyse statistique, théorie des probabilités et l'analyse des données. Cela inclut les tests statistiques standard, l'analyse des corrélations et la conception expérimentale. Il introduit des méthodes statistiques informatiques pour analyser de grands ensembles de données. Quan
Vittorio ErbaEnseignement et PhD Cours Statistical physics of computation PHYS-512 Les étudiants comprennent les outils de la physique statistique des systèmes désordonnés et les appliquent pour étudier des problèmes d'informatique et de statistiques en théorie des graphes, en optimisation discrète, ainsi qu'en inférence et en apprentissage automatique.
Antoine BosselutAntoine Bosselut is an assistant professor at EPFL. He leads the EPFL NLP group, which conducts research on natural language processing (NLP) systems that can model, represent, and reason about human and world knowledge.
Prior to joining EPFL, he was a postdoctoral researcher at Stanford University working in the
SNAP
and
NLP
groups and a young investigator on the
Mosaic
project at the
Allen Institute for AI
. He completed his PhD at the University of Washington.
Vladimir ManucharyanEnseignement et PhD Doctorant·es actuel·les Chulwoo Ahn, Marco Nicolas Mueller, Taketo Imaizumi, Andrea Lizzit, Andrea Duina, Nikola Dimitrov Dimitrov Cours Microwave engineering in physics QUANT-410 Ce cours vise à enseigner les notions de base et les astuces de l'ingénierie des micro-ondes aux étudiants n'ayant qu'une connaissance élémentaire de l'électromagnétisme. L'accent est mis sur des sujets qui apparaissent souvent dans les expériences de physique moderne, y compris la science qua
Michael HerbstSee also
https://matmat.org: Group websitehttps://michael-herbst.com: Blog & personal website
Enseignement et PhD Doctorant·es actuel·les Niklas Frederik Schmitz, Anna Paulish, Bruno Ploumhans, Benedikt Menges Cours Error control in scientific modelling MATH-500 Les erreurs sont omniprésentes dans les sciences informatiques. En ce qui concerne les problèmes de valeurs propres motivés par la science des matériaux et la modélisation atomistique, nous discutons, mettons en œuvre et appliquons Han SunExpertise
Deep Learning, Computer Vision, Domain Adaptation, Generative Modeling
Open Projects:
Test-Time Domain Adaptation for Anomaly Detection: SiROP link for detailed information
Han obtained her master's degree in Geomatic from the Federal Institute of Technology in Zürich (ETHZ). Before joining IMOS Lab - EPFL, she focused on computer vision with a particular interest in domain adaptation & style adaptation. During her Ph.D. study, she will explore more in the field of domain adaptation with its appli
Sanggyu ChongSanggyu "Raymond" Chong obtained his BS, MS and PhD degrees in Chemical and Biomolecular Engineering from Korea Advanced Institute of Science and Technology (KAIST), where he primarily focused on the computational design of metal-organic frameworks for applications ranging from gas storage to functional electronics. In March 2022, Sanggyu joined COSMO as a postdoctoral researcher, and he is currently investigating the robustness of local and/or component-wise predictions made by atomistic machine learning m
