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
Francesca RodinoExpertise
Electrochemical BiosensorsSensors and Biosensors interfaces | front-end electronicsBiomedical circuits and systems
RechercheOther Tavakolidakhrabadi, A., Domange, T., Nalm, C., Rodino, F., Meimandi, A., Bessire, C., & Carrara, S. (2024). A Novel Microfluidic System for Capacitive Detection via Magnetophoretic Separation of Malaria-Infected Red Blood Cells. IEEE Sensors Letters. DOI: 10.1109/LSENS.2024.3451238Barbruni, G. L., Rodino, F., Ros, P. M., Demarchi, D., Ghezzi, D., & Carrara, S. (2024). A
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
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
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.
Michail VlachosEnseignement et PhD Cours Data science and machine learning MGT-502 Introduction pratique à la science des données et à l'apprentissage automatique. Nous abordons les systèmes de recommandation, l'IA générative, les chatbots, les graphes, ainsi que la régression, la classification, l'analyse de texte et les réseaux neuronaux. Programmation en Python.
Alexander DittrichCurrent Work
My research interests are somewhere between neural networks with Hebbian plasticity, meta-reinforcement learning, and the control of rather unconventional soft robotic platforms like tensegrity robots.
Sanggyu ChongSanggyu "Raymond" Chong obtained his BS, MS and PhD degrees in Chemical and Biomolecular Engineering from Korea Advanced Institute of Science and Technology (KAIST), where he primarily focused on the computational design of metal-organic frameworks for applications ranging from gas storage to functional electronics. In March 2022, Sanggyu joined COSMO as a postdoctoral researcher, and he is currently investigating the robustness of local and/or component-wise predictions made by atomistic machine learning m
Konstantinos KarapiperisEnseignement et PhD Doctorant·es actuel·les Hrishikesh Gopakumar Menon, Thomas Henzel Cours Multiscale modelling in mechanics CIVIL-408 Ce cours présente les principes et techniques de modélisation des matériaux à différenteséchelles spatiales, depuis le niveau des atomes ou des grains jusqu'à l'échelle continue oustructurelle. L'accent est mis sur la mise à l'échelle hiérarchique (homogénéisation),tandis que les techniques concu Soil mechanics and flow through porous media CIVIL
