Clément Pit-ClaudelTeaching & PhD PhD Students Yawen Guan, Kacper Feliks Korban, Can Cebeci, Alexandre Pinazza, Shardul Chiplunkar Courses Interactive Theorem Proving Project CS-642 A project-focused introduction to interactive theorem proving. Interactive theorem proving CS-428 A hands-on introduction to interactive theorem proving, computer-checked mathematics, compiler verification, proofs as programs, dependent types, and proof automation.Come learn how to write computer-checked proofs an
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,
Parmenion MavrikakisExpertise
Computational electromagnetics, integral equations, finite element analysis, metasurfaces, photonics, plasmonics and microwaves.
Current Work
Developing a C++ code for the modeling of light scattering in layered media with the surface integral equation method.
I am a PhD student in the Electrical Engineering Department (EDEE) at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Nanophotonics and Metrology Laboratory (NAM), part of the Microengineering Department (IEM) at EPFL. M
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
Mats Julius StensrudTeaching & PhD PhD Students Ignacio Gonzalez Perez, Gellért Géza Perényi, Lorenzo Gasparollo, Julien David Laurendeau Past EPFL PhD Students Matias Janvin, Amit Sawant Courses Causal thinking MATH-352 This course will give a unified presentation of modern methods for causal inference. We focus on concepts, and we will present examples and ideas from various scientific disciplines, including medicine, computer science, engineering, economics and epidemiology. Probability and statistics (
Robert WestRobert West is a tenure-track assistant professor of computer science at EPFL, where he heads the Data Science Lab. In his research, he develops and applies techniques in machine learning, computational social science, natural language processing, social network analysis, and data mining. Bob also collaborates closely with the Wikimedia Foundation, in his role as a Wikimedia Research Fellow. Bob’s work has won several awards, including best/outstanding paper awards at ICWSM’21, ICWSM’19, and WWW’13, a best-paper runner-up award at WWW’16, a Google Faculty Research Award, a Facebook Research Award, a Hewlett-Packard Graduate Fellowship, and a Facebook Graduate Fellowship. He is actively involved in the research community, e.g., as an Associate Editor of ICWSM and EPJ Data Science and as a co-founder of the Wiki Workshop (held at WWW and ICWSM) and the Applied Machine Learning Days. Bob received his PhD in Computer Science from Stanford University, his MSc from McGill University, Canada, and his undergraduate degree from Technische Universität München, Germany.[Last updated: 25 Aug 2021]
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
Sahand Jamal RahiExpertise
- Biophysics- Statistical mechanics- Systems biology- Computational biology- Genetics
Teaching & PhD PhD Students Alisa Gross, Matthieu Schmidt, Marco Labagnara, Lorenzo Scutteri, Haozong Zeng Past EPFL PhD Students Ahmad Sadeghi, Mahsa Barzegarkeshteli, Vojislav Gligorovski, Roxane Oesterle Courses Biophysics : physics of biological systems PHYS-302 Understand and use the results and methods of population genetics, population dynamics, network theory, and reaction network dynami
Emma Elizabeth TolleyI studied the universe at the smallest scales at the Large Hadron Collider, now we're getting ready to study it at the largest scales with the Square Kilometer Array. My research focuses on developing high-performance computing and new data science techniques to image and analyse the radio sky.
Teaching & PhD PhD Students Markus Johan Bredberg, Ashutosh Kumar Mishra Past EPFL PhD Students as codirector Shreyam Parth Krishna Courses General physics : mechanics (english flipped classroom) PHYS-101
Annalisa BuffaTeaching & PhD PhD Students Gonzalo Bonilla Moreno, Philipp Christoph Weder, Yannis Dirk Voet, Fabio Marcinno, Ferhat Sindy, Francesco Sala, Markus Renoldner, Mohamed Ben Abdelouahab, Davor Dobrota Past EPFL PhD Students Luca Coradello, Ondine Chanon, Riccardo Puppi Courses Numerical approximation of PDEs MATH-451 The course is about the derivation, theoretical analysis and implementation of the finite element method for the numerical approximation of partial differential equations in on
Martin Alois RohrmeierTeaching & PhD PhD Students Joris Monnet, Marina Borsodi-Benson, Xinyi Guan, Xiaoxuan Wang, Zeng Ren Past EPFL PhD Students Fabian Claude Moss, Daniel Harasim, Christoph Finkensiep, Johannes Hentschel, Gabriele Cecchetti, Shuxin Meng Courses Digital musicology DH-401 This course will introduce students to the central topics in digital musicology and core theoretical approaches and methods. In the practical part, students will carry out a practical project. Musical theory and creativity
Carmela González TroncosoSPRING Lab
Our research focuses on building secure and privacy-preserving systems. We aim to develop tools and methodologies to help engineers embedding strong security and privacy guarantees in their designs, as well as techniques that help them to systematically quantifying the information that an adversary can infer from data she may have access to.More information about our activities here: https://spring.epfl.ch/
Teaching & PhD PhD Students Saiid El Hajj Chehade, Eric Jollès, Christian Knabenhans, Boy 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.
Andrea VezzosiAndrea Vezzosi is a postdoctoral researcher in the group of Prof. Ursula Rothlisberger at the Institute of Chemical Sciences and Engineering, EPFL (Switzerland). He earned his Ph.D. in Physics and Nanosciences from the University of Modena and Reggio Emilia in 2024, where he investigated spin–orbit coupling and topological states in core–shell semiconductor nanowires. During his doctoral studies, he developed nwkp, an open-source Python library for computing the band structure of core–shell nanowires using
Ayberk OzkirliDr. Ayberk Ozkirli is a vision neuroscientist whose research investigates how spatiotemporal context influences visual perception.He completed his PhD in Neuroscience at the Laboratory of Psychophysics at EPFL in 2025, under the supervision of Prof. Michael Herzog and Prof. David Pascucci. He holds an M.Sc. in Bioengineering from EPFL (Switzerland) and a B.Sc. in Electrical and Electronics Engineering from Bilkent University (Turkey).His expertise spans neuroimaging, statistics, experimental design, neural
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.
Olga FinkTeaching & PhD PhD Students Han Sun, Leandro Von Krannichfeldt, Keivan Faghih Niresi, Zepeng Zhang, Vinay Sharma, Chenghao Xu, Raffael Pascal Theiler, Kevin Antonio Steiner, Sergei Garmaev, Amaury Wei Past EPFL PhD Students Ismail Nejjar, Mengjie Zhao Courses Data Science for infrastructure condition monitoring CIVIL-332 The course will cover the relevant steps of data-driven infrastructure condition monitoring, starting from data acquisition, going through the steps pre-processing of real
