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
Camille Véronique Bernadette GoemansCamille's research focuses on understanding how antibiotics and non-antibiotic drugs affect the diverse bacteria from the human gut microbiota and how they contribute to dysbiosis and the development of antibiotic resistance. To achieve this goal, she combines systems approaches with molecular microbiology, bacterial genetics and biochemistry.She obtained her Bachelor's and Master's degrees in Biomedical Sciences from the UCLouvain, Belgium, after which she completed her PhD (FRIA national fellowship) at th
Ianina AltshulerTeaching & PhD PhD Students Haohua He, Anna Dukat, Laureen Sarah Ahlers, Anastasiia Kosolapova, Grace Emma Marsh Courses Biology ENV-103 This course will cover the fundamental principles governing life and the living world. Topics will include the diversity of living organisms, cellular biology, genetics, evolution, and ecology. This course provides a foundation in biology, fostering critical thinking & analytical skills. EESS - CESS Seminar Course - option 1 (FALL) ENV-630(a)
Milena Maria SchuhmacherResearchSchuhmacher Lab & Chemical and Membrane Biology It's all about the lipids: In the Schuhmacher Lab we are interested in answering outstanding questions in membrane biology. Our chemical biology approach opens the door to investigate the so far mostly invisible and thus secret work of lipids. In particular, we would like to understand the biological role of lipid diversity and their impact on signaling processes.
Teaching & PhD PhD Students Mélissa Ruiz, Gary Domeniconi, Linda Wedemann Courses
Prabhu Prasad SwainEducation Integrated M.Sc. (5 year) | Physics (majors)Chemistry, Biology, Mathematics and Electronics (minors) 2015 – 2020 UM-DAE Centre for Excellence in Basic Sciences, Mumbai
Nicolas ThomäTeaching & PhD PhD Students David Domjan, Pierre Alexander Miranda Herrera, Laurin Tim Kanis, Alessandro Minafra, Pau Reolid Coll Courses Practical - Thomä Lab BIO-624 Expression and purification of recombinant proteins are key methods in our lab studying protein machines on a structural level and ways in which they can be reprogrammed by small molecules. In the course, we will express and purify proteins and biophysically characterise them. Trends in chemical biology and drug discovery
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 (
Aleksandar AntanasijevicTeaching & PhD PhD Students Camilla Di Giulio, Kiruthika Kumar, Yash Garodia Courses Biological chemistry I BIO-212 Biochemistry is a key discipline for the Life Sciences. Biological Chemistry I and II are two tightly interconnected courses that aim to describe and understand in molecular terms the processes that make life possible. General chemistry for SV CH-100 This course covers essential notions in general chemistry, relative to matter and its structure, equilibriums
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
Vittorio ErbaTeaching & PhD Courses Statistical physics of computation PHYS-512 The students understand tools from the statistical physics of disordered systems, and apply them to study computational and statistical problems in graph theory, discrete optimisation, inference and machine learning.
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•
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.
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
Andrew James SontaExpertise
Human-building interaction, building energy, occupant behavior, sustainable design and planning, walkability, network analysis, machine learning, urban informatics, social systems.
Andrew Sonta is a tenure track assistant professor of sustainable civil engineering at EPFL. He directs the ETHOS Lab: Engineering and Technology for Human Oriented Sustainability. ETHOS is an interdisciplinary research group focused on using data-driven and computational tools to create interventions in the built envir
Satyam TiwariExpertise
Protein biophysics, Protein Engineering, Chaperone biology, Protein folding, Protein misfolding diseases , Statistical Data Analysis, Cell molecular biolgy
Mission
I employ biophysics and protein biochemistry to address and comprehend protein misfolding and aggregation. The goal is to design molecular chaperone-based disaggregases (protein drugs, biotherapeutics) targeted at disease-specific protein aggregates. I am currently investigating TDP-43 misfolding and amyloid formation (this protein aggr
Edoardo ChiarottiTeaching & PhD Courses Data Science & Causal Inference for Sustainability MGT-499 This class explores key climate questions through data. Students will learn to collect, clean, and analyze data, apply causal methods using Python, and communicate insights clearly. With a focus on sustainability, the course builds skills to avoid pitfalls and draw meaningful conclusions.
Giuseppe CarleoGiuseppe Carleo is a computational quantum physicist, whose main focus is the development of advanced numerical algorithms tostudy challenging problems involving strongly interacting quantum systems.He is best known for the introduction of machine learning techniques to study both equilibrium and dynamical properties,based on a neural-network representations of quantum states, as well for the time-dependent variational Monte Carlo method.He earned a Ph.D. in Condensed Matter Theory from the International School for Advanced Studies (SISSA) in Italy in 2011.He held postdoctoral positions at the Institut d’Optique in France and ETH Zurich in Switzerland, where he alsoserved as a lecturer in computational quantum physics.In 2018, he joined the Flatiron Institute in New York City in 2018 at the Center for Computational Quantum Physics (CCQ), working as a Research Scientist and project leader, and also leading the development of the open-source project NetKet.Since September 2020 he is an assistant professor at EPFL, in Switzerland, leading the Computational Quantum Science Laboratory (CQSL).
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
