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.
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
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
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
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
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•
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
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
Wenlong LiaoExpertise
deep learning, power system, renewable energy, data analysis
Lazar MilikicExpertise
LLMs (Large Language Models), NLP (Natural Language Processing), Automated Reasoning
Mission
My work focuses on developing robust methods for autoformalization and automated theorem proving using large language models. I aim to enhance the reasoning reliability of modern AI systems by reducing hallucinations, improving predictability, and integrating formal verification techniques and tools into LLM-based pipelines.
Before joining EDIC, I completed a Bachelor’s in Mathematics and Computer Science
Siba Smarak PanigrahiExpertise
Geometric Deep Learning, Generative Models
I am a Ph.D. at école Polytechnique Fédérale de Lausanne (EPFL) working with Prof. Maria Brbic in the Brbic Lab. My research interests span geometric deep learning, generative models, and computer vision.Previously, I was a visiting researcher at ServiceNow Research in the Multimodal Foundation Models team, building foundation model for structured document understanding. I was also a Research Intern at PROSE at Microsoft, working on designing algorithms a
Andrea CavalliEnseignement et PhD Doctorant·es actuel·les Alessia Ghidini Cours Drug Discovery CH-630
Maryam KamgarpourEnseignement et PhD Doctorant·es actuel·les Giulio Salizzoni, Tingting Ni, Saurabh Dilip Vaishampayan, Andreas Schlaginhaufen, Kai Ren, Anna Maria Maddux, Gabriel Vallat, Philip Jordan, Yasaman Zolfimoselo, Daniele De Cecco, Gregorio Valenti A co-dirigé les thèses EPFL de Baiwei Guo Cours Foundations of artificial intelligence ME-390 Ce cours fournit aux étudiants la théorie de base pour comprendre l'approche de l'apprentissage automatique (machine learning), et les outils pour utiliser l'
