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
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.
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
Benjamin Alexander Kellenberger2020–: Postdoctoral Researcher, EPFL, Sion, Switzerland2020: Postdoctoral researcher, Wageningen University, Netherlands2017–2020: PhD (cont'd); Wageningen University, Netherlands2016–2017: PhD; University of Zurich, Switzerland2009–2014: BSc. and MSc. in geography (remote sensing and GIS) and computer science; University of Zurich, Switzerland
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
Laurence DanguyChercheuse FNS senior à l’Université de Lausanne, chercheuse associée au Centre d’histoire du XIXe siècle de Paris I-IV (Isor) et au Centre d’étude de l’écriture et de l’image (CEEI). Docteure de l’Ehess et de l’Université de Constance. Collaboration à l’Unil depuis 2008, chargée de cours à l’Université de Constance entre 2005 et 2009, chargée de conférences de 2010 à 2012 à l’Ehess, puis de 2016 à 2018, chargée de cours à l’Epfl depuis 2020. Recherches actuelles sur les revues illustrées européennes ainsi que sur l’image populaire dans le champ artistique européen. Thèse de doctorat parue sous le titre
L’Ange de la jeunesse – La revue
Jugend
et le Jugendstil munichois
(MSH, collection Philia, 2009). Monographie L
e Nebelspalter zurichois (1875/1921). Au cœur de l’Europe des revues et des arts
, issue d’un projet Unil/FNS ( Droz, collection Presse et caricature, 2018).
Liste des publications :
https://applicationspub.unil.ch/interpub/noauth/php/Un/UnPers.php?PerNum=1066210&LanCode=37&menu=pub
Page Unil :
https://www.unil.ch/hart/fr/home/menuinst/collaborateurs-1/ancienne-page-collaborateurs/histoire-de-lart-contemporai/laurence-danguy.html 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
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
Afficher plus