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
Carmela González TroncosoEnseignement et PhD Doctorant·es actuel·les Saiid El Hajj Chehade, Eric Jollès, Christian Knabenhans, Boya Wang, Mathilde Aliénor Raynal A dirigé les thèses EPFL de Sandra Deepthy Siby, Sylvain Chatel, Christian Vincent Mouchet, Bogdan Kulynych, Kasra Edalatnejadkhamene, Sinem Sav, Theresa Stadler, Klim Kireev Cours Privacy at the communication layer CS-721
Alessandro ChiesaAlessandro Chiesa is a faculty member in computer science. He conducts research in complexity theory, cryptography, and security, with a focus on the theoretical foundations and practical implementations of cryptographic proofs that are short and easy to verify. He is a co-author of several zkSNARK libraries, and is a co-inventor of the Zerocash protocol. He has co-founded Zcash and StarkWare Industries. He is a recipient of a Sloan Research Fellowship (2021), an Okawa Foundation Research Grant (2020), and Google Faculty Research Awards (2018 and 2017). He was included in MIT Technology Review's "35 Innovators Under 35" list in 2018.
Ehsan PajouheshgarExpertise
Computer Vision, Computer Graphics, Complex Systems, Machine Learning
Education Bachelor of Science | Major: Computer EngineeringMinor: Mathematics 2015 – 2020 Sharif University of Technology Computer Science | 2020 – 2025 EPFL Directed by Sabine Süsstrunk
Awards Teaching Assistance Excellence Award EPFL 2023 Best Student Paper Award From ALife 2024 Conference ALife 2024 Conference 2024 Best Paper Award From SIGGRAPH 2022 Conference ACM
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
Sanidhya KashyapSanidhya Kashyap is a systems researcher and an assistant professor at the EPFL School of Computer and Communication Sciences (IC). His research focuses on designing systems software that are performant and robust for heterogeneous hardware. He is broadly interested in the area of systems with a particular focus on operating systems, databases, concurrency, scheduling, networks, data analytics, and software testing (fuzzing).
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•
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
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
Ayatallah Ahmed Gamal Kamal ElakhrasExpertise
Dataflow ArchitectureHigh-Level Synthesis
Ayatallah is a Ph.D. student in the Processor Architecture Laboratory, advised by Professor Paolo Ienne. Between October 2023 and March 2024, she did an internship at AMD in the Research and Advanced Development team, under the supervision of Dr. Kristof Denolf. She received a B.Sc. degree in Computer Engineering from the American University in Cairo, Egypt in 2020 and started her Ph.D. in the same year.Her research interests include dataflow architecture,
Mika Tapani GöösEnseignement et PhD Doctorant·es actuel·les Valentin Imbach, Ziyi Guan, Artur Riazanov, Anastasiia Sofronova, Weiqiang Yuan A dirigé les thèses EPFL de Maystre Gilbert Théodore Cours Computational complexity CS-524 En théorie de la complexité, nous étudions les ressources nécessaires à résoudre des problèmes et les relations entre différents modèles de calcul.Ce cours donne une meilleure connaissance de la complexité informatique et aborde les questions ouvertes fondamentales.
Nicolas Henri Bernard FlammarionNicolas Flammarion is a tenure-track assistant professor in computer science at EPFL. Prior to that, he was a postdoctoral fellow at UC Berkeley, hosted by Michael I. Jordan. He received his PhD in 2017 from Ecole Normale Superieure in Paris, where he was advised by Alexandre d’Aspremont and Francis Bach. In 2018 he received the prize of the Fondation Mathematique Jacques Hadamard for the best PhD thesis in the field of optimization. His research focuses primarily on learning problems at the interface of machine learning, statistics and optimization.
Dimitrios KaryampasEnseignement et PhD Cours Financial applications of blockchains and distributed ledgers FIN-413 Ce cours propose une introduction à la technologie des registres distribués, aux blockchains et aux crypto-monnaies, ainsi qu'à leurs applications dans le domaine de la finance et de la banque. L'objectif est d'établir des analogies entre la finance traditionnelle (TradFi) et les crypto-monnaies.
Xavier Eric OuvrardProfessionals experiences IT System Specialist IT System Specialist in charge of the Experiment Facility of EcoCloud 2022–2022 EPFLHPC cluster system specialist Working as System specialist for the Radio Protection department: managing HPC cluster for FLUKA simulations for radio-protection.Full-Stack developer for the Radio-Analytical Laboratory of CERN: developed a web application to characterize low radioactive waster 2020–2022 CERNResearch assistant Working in doctoral position at CERN on Collaboration
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.
