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
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
Zepeng ZhangZepeng is a PhD student at École Polytechnique Fédérale de Lausanne (EPFL). He works in the Intelligent Maintenance and Operations Systems (IMOS) Lab under the supervision of Prof. Olga Fink. Previously, He received his master’s degree at ShanghaiTech University and B.Eng. degree from Wuhan University (WHU). During his studies, he have visited Télécom Paris, Institut Polytechnique de Paris (IP Paris), Peking University (PKU), and City University of HongKong (CityU) as a research intern. His current research
Ernst HardyEnseignement et PhD Cours Non-destructive methods for industry and research MSE-668
Annapaola ParrilliEnseignement et PhD Cours Non-destructive methods for industry and research MSE-668
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•
Leonid MoninEnseignement et PhD Cours Algebra III - rings and fields MATH-215 C'est un cours introductoire dans la théorie d'anneau et de corps. Analyse I (anglais) MATH-101(en) Étudier les concepts fondamentaux d'analyse et le calcul différentiel et intégral des fonctions réelles d'une variable. Topology III - Homology MATH-323 L'homologie est l'un des outils les plus importants pour étudier les espaces topologiques et elle joue un rôle important dans de nombreux domaine
Tim Ruben DavidsonExpertise
deep generative models; agentic systems; synthetic data; representation learning
Mission
I study how deep generative models can be used to power agentic systems and generate useful synthetic data
Rajita Ramesh ChandakExpertise
L'estimations non parametrique, théorie de l'apprentissage automatique, l'inférence statistique.
Enseignement et PhD Cours Nonparametric estimation and inference MATH-524 Les modèles non paramétriques sont utilisés pour identifier les relations non linéaires au sein des données. Ce cours donne un aperçu de l'estimation statistique et de la théorie de l'inférence non paramétrique. Statistical inference MATH-562 L'inférence du particulier au général basée sur des modè
Pedro Correa FernandezPedro Correa Fernández is a Doctoral Candidate in Architecture at Columbia GSAPP. Before joining GSAPP, he was an adjunct professor at the Architecture School of Universidad Católica de Chile where he taught seminars and lectures on architecture history and related epistemological, aesthetic, and political issues. His current work examines the mediations between technical knowledge, artisanal crafts, and global industrial capitalism in early nineteenth-century Latin America.Pedro holds an architecture degre
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
Julie Nathalie S GheysenEnseignement et PhD Cours Comportement mécanique des matériaux MSE-234 Ce cours est une introduction au comportement mécanique, à l'élaboration, à la structure et au cycle de vie des grandes classes de matériaux de structure (métaux, polymères, céramiques et composites) Matériaux MSE-171 Une introduction à la science des matériaux appliquée aux matériaux de construction courants, en particulier le béton et les métaux. Description de leur fabrication, leurs comportements mécan
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
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
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
Caglar GulcehreEnseignement et PhD Doctorant·es actuel·les Tim Ruben Davidson, Skander Moalla, Anja Surina, Xiuying Wei, Liangze Jiang, Mikhail Terekhov, Amin Mansouri, Justin Samuel Deschenaux, Yitao Xu Cours Training Large Language Models EE-628
Sayan BiswasExpertise
Decentralized Learning; Federated Learning; Ethical ML focusing on Privacy, Fairness, and Personalization; Location Privacy.
I am a Postdoctoral Researcher at the SaCS lab at EPFL. I completed my PhD in Computer Science from INRIA and école Polytechnique in France, under the supervision of Catuscia Palamidessi. Previously, I have been a Visiting Scholar at the School of Computing at Macquarie University in Sydney, Australia, collaborating with Annabelle McIiver and Natasha Fernandes, and at WMG, t
Wenlong LiaoExpertise
deep learning, power system, renewable energy, data analysis
