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
Myrto LimniosExpertise
Nonparametric statistics, statistical learning theory and methods, stochastic processes
Enseignement et PhD Cours Empirical processes MATH-522 Nous étudierons comment contrôler le comportement non-asymptotique et aléatoire de collections d'estimateurs, lorsqu'indexées par des classes de fonctions/d'ensembles. Des exemples en statistiques et des méthodes non-paramétriques en apprentissage automatique seront traités. Regression methods MATH-408 Cours de niveau master
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
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.
Federico AmatoI have an MSc in Engineering and a Ph.D. in Sustainable Development and Innovation Engineering. After a three-year Postdoc in Environmental Data Mining, in 2021 I joined the Swiss Data Science Centre, a joint venture between the polytechnical schools of Lausanne (EPFL) and Zurich (ETH) having as mission the acceleration of the digital transformation of the academic community and the industrial sector, putting to work Artificial Intelligence and Machine Learning and facilitating the multidisciplinary exchange of data and knowledge.
Over the years I worked on the development of methodological tools to mine and model big spatiotemporal datasets. I extensively applied such methods to study the interaction between the spatial and temporal components of environmental and geographical phenomena, and their consequences in terms of spatial planning and urban geography. My academic activity has focused on the analysis of land-use dynamics and their relationship with climate, pollution, natural hazards, and other social/economic phenomena. I have deep competencies in applied statistics, machine learning, geocomputation, spatial statistics, urban modeling, and remote sensing. I am also an expert in European Project development and implementation.
Pawel DuchExpertise
My present research focuses on the intersection between probability theory, PDE theory and Euclidean quantum field theory. I am especially interested in problems involving singular stochastic partial differential equations and renormalization. I have also a background in mathematical aspects of perturbative and axiomatic quantum field theory as well as general relativity.
I am a postdoctoral researcher in the group of Martin Hairer. Previously, I was a postdoc at Adam Mickiewicz University in Pozn
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
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
Baraka Jean-Claude MunyakaExpertise
Transport modelling, Logistics, Supply Chain Systems, and Urban Planning, Geospatial Analysis, Lean Manufacturing
Dr. Jean-Claude Munyaka Baraka is a Research Collaborator at the Urban and Regional Planning Community (CEAT) at the Swiss Federal Institute of Technology in Lausanne (EPFL). A citizen of the Democratic Republic of Congo, Dr. Munyaka holds a Doctorate in Industrial and Systems Engineering from the University of Pretoria, South Africa, and earned his Master's degree with Cum Laude in th
Yunxuan SongEnseignement et PhD Cours Projet de master en physique PHYS-599(b) L'étudiant·e réalise un projet de recherche en physique en relation directe avec les scientifiques d'un laboratoire ou en entreprise.
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
Georg Michael Joachim StarkeDr. Georg Starke is a postdoctoral researcher at the College of Humanities at EPFL, working in the
Intelligent Systems Ethics Group
. As member of the
Hybrid Minds
project, Georg’s research examines the ethics of using artificial intelligence in medicine, with particular regard to neurological and psychiatric applications. Beyond AI ethics, Georg is also interested in history and philosophy of science, philosophy of psychiatry, medical ethics, and questions at the intersection of philosophy of mind and comparative psychology.
Georg has been trained in medicine and in philosophy, concluding both studies with a respective doctoral degree. He studied medicine at the Technical University of Munich and was visiting student at the University of Buenos Aires, the Hebrew University Jerusalem, and the University of Oxford. His medical doctoral thesis investigated subcortical correlates of social fear, using model-based fMRI. In parallel to his medical studies, Georg obtained a BA in philosophy from the Munich School of Philosophy and an MPhil in History, Philosophy and Sociology of Science, Technology and Medicine from the University of Cambridge. His PhD in bioethics at the University of Basel, defended in 2022, shed light on the notion of trust in medical AI and scrutinized the trustworthiness of clinical AI appliances with particular view to fairness and explainability.
Andrea CavalliEnseignement et PhD Doctorant·es actuel·les Alessia Ghidini Cours Drug Discovery CH-630
