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
Stefana ParaschoEnseignement et PhD Doctorant·es actuel·les Jingwen Wang, Gabriel Vallat, Maxence Grangeot, Eleni Maria Skevaki, Wenqian Yang, Megi Sinani Cours Capitalizing on Uncertainty AR-809 Digital design and making: A critical introduction AR-503 Le cours présente des méthodes de conception et de fabrication numériques en combinant des compétences techniques avec des connaissances théoriques et une réflexion critique. Les sujets incluent: la programmation pour la conception, la fabr
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
Ehsan PajouheshgarExpertise
Computer Vision, Computer Graphics, Complex Systems, Machine Learning
Education Bachelor of Science | Major: Computer EngineeringMinor: Mathematics 2015 – 2020 Sharif University of Technology Computer Science | 2020 – 2025 EPFL Directed by Sabine Süsstrunk
Awards Teaching Assistance Excellence Award EPFL 2023 Best Student Paper Award From ALife 2024 Conference ALife 2024 Conference 2024 Best Paper Award From SIGGRAPH 2022 Conference ACM
Keivan Faghih NiresiExpertise
Computational sensing/imaging, Inverse problems, Signal processing, Graph neural networks, Domain adaptation.
Keivan is a PhD student at école Polytechnique Fédérale de Lausanne (EPFL). He joined the Intelligent Maintenance and Operations Systems (IMOS) Lab under the supervision of Prof. Olga Fink in February 2023.Prior to joining EPFL, he obtained his master's degree from the Institute of Communications Engineering, College of Electrical Engineering and Computer Science, National Tsing Hua Univer
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
Andrea VezzosiAndrea Vezzosi is a postdoctoral researcher in the group of Prof. Ursula Rothlisberger at the Institute of Chemical Sciences and Engineering, EPFL (Switzerland). He earned his Ph.D. in Physics and Nanosciences from the University of Modena and Reggio Emilia in 2024, where he investigated spin–orbit coupling and topological states in core–shell semiconductor nanowires. During his doctoral studies, he developed nwkp, an open-source Python library for computing the band structure of core–shell nanowires using
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.
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•
Giuseppe CarleoTwitter
https://twitter.com/gppcarleo
Enseignement et PhD Doctorant·es actuel·les Gian Gentinetta, Linda Mauron, Samuele Piccinelli, Alessandro Sinibaldi, Shao Hen Chiew, David Linteau, Clemens Giuliani, Ali Goodarzi, Gianluca Grosso, Ruize Ma, Ekaterina Pankovets A dirigé les thèses EPFL de Dian Wu, Julien Sebastian Gacon, Gabriel Maria Pescia, Barison Stefano, Imelda Romero Cours Advanced computational physics PHYS-339 Le cours couvre l'algèbre linéaire dense/creuse, les méthodes variati Parmenion MavrikakisExpertise
Computational electromagnetics, integral equations, finite element analysis, metasurfaces, photonics, plasmonics and microwaves.
Current Work
Developing a C++ code for the modeling of light scattering in layered media with the surface integral equation method.
I am a PhD student in the Electrical Engineering Department (EDEE) at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Nanophotonics and Metrology Laboratory (NAM), part of the Microengineering Department (IEM) at EPFL. M
Vivek SubramanianEnseignement et PhD Doctorant·es actuel·les Giovanni Ruffolo, Giada Romano, Sanjay Manoharan, Kyle Haas, Claude Dahan, Biruktait Ayele Lemecho, Yagmur Ceren Alatas, Tugçe Delipinar A dirigé les thèses EPFL de Amin Hodaei, Mustafa Mohieldin Fadlelmula Fadlelseed A co-dirigé les thèses EPFL de Mohammad Jafarpour Cours Organic and printed electronics MICRO-505 Ce cours traite de la mise en œuvre des technologies de l'électronique organique et imprimée: les matériaux, les procédés d'impression
Athanasios NenesEnseignement et PhD Doctorant·es actuel·les Berkay Dönmez, Ernest Abboud A dirigé les thèses EPFL de Paraskevi Georgakaki, Lucile Ricard Cours Atmospheric processes: from cloud to global scales ENV-407 L'objectif principal est de voir les processus atmosphériques les plus importants de l'échelle locale à l'échelle globale. Le cours démarrera avec les processus nuageux, continuera avec les phénomènes synoptiques comme les cyclones extratropicaux et fronts, pour finir par la modélisation num
Geovani RizkExpertise
Distributed Machine Learning, Robustness, Safety, Optimization, Multi-Agent, Bandits in Graphs
I am a postdoctoral researcher at école Polytechnique Fédérale de Lausanne since 2022, where I work with Rachid Guerraoui on robustness of distributed machine learning algorithms. From 2018 to 2022, I completed my Ph.D. in computer science at Université Paris Dauphine-PSL on multi-agent bandits in graphs under the supervision of Yann Chevaleyre, Rida Laraki, Igor Colin, and Albert Thomas.Pre-prints Over
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
Mika Tapani GöösEnseignement et PhD Doctorant·es actuel·les Valentin Imbach, Ziyi Guan, Artur Riazanov, Anastasiia Sofronova, Weiqiang Yuan A dirigé les thèses EPFL de Maystre Gilbert Théodore Cours Computational complexity CS-524 En théorie de la complexité, nous étudions les ressources nécessaires à résoudre des problèmes et les relations entre différents modèles de calcul.Ce cours donne une meilleure connaissance de la complexité informatique et aborde les questions ouvertes fondamentales.
Ayberk OzkirliExpertise
Magnetic resonance imaging (MRI), visual crowding, serial dependence, population receptive field (pRF) mapping, data analysis, machine learning, age-related macular degeneration, neuroengineering, clinical neuroscience
Expertise
Magnetic resonance imaging (MRI), visual crowding, serial dependence, population receptive field (pRF) mapping, data analysis, machine learning, age-related macular degeneration, neuroengineering, clinical neuroscience
Lénaïc ChizatEnseignement et PhD Doctorant·es actuel·les Javier Esteban Maass Martinez A dirigé les thèses EPFL de Guillaume Yitian Wang Cours Computational optimal transport MATH-528 Aspects computationnels de la théorie du transport de mesures, du problème classique du transport optimal classique au modèles de diffusion modernes. Topics in machine learning MATH-520 Analyse mathématique des techniques modernes d'apprentissage supervisé, avec une emphase sur les réseaux de neurones arti
Paul Robert GuhennecMes recherches portent sur l'utilisation de méthodes informatiques pour l'histoire de l'architecture et leurs implications épistémologiques. Je suis actuellement chercheur post-doctoral au Digital Humanities Laboratory de l'EPFL, où j'ai récemment terminé ma thèse de doctorat sur l'histoire urbaine et architecturale de Venise, intitulée «The Skin of Venice: A Computational Approach to the City's Urban Structure».
