Anne-Florence Raphaëlle BitbolI was trained in physics, and always had a strong interest in biology. I am broadly interested in understanding biological phenomena in a quantitative way, through physical concepts and mathematical and computational tools. I investigate the relative impacts of optimization and historical contingency in biological evolution, both at the scale of protein sequences and at the scale of microbial populations.Here is my research group website.Curriculum vitae Here is my complete CV. Professional experience:Since
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
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
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
Mykhailo BatiukExpertise
Single cell and spatial genomics (wet/dry lab), glia, psychiatry, neuroscience
I obtained my PhD (2012-2018) in KU Leuven/VIB, Belgium where I investigated astrocyte heterogeneity using single cell transcriptomics. During this period I developed tools to acutely and specifically isolate astrocytes from adult brain and identified five astrocyte subtypes in the cortex and hippocampus of mouse brain expanding previous understanding of astrocyte variability.Following my PhD, I did my first post-doc in
Vincenzo PalatellaTeaching & PhD Courses Information literacy for chemists ENG-619 Concepts and tools to understand and use the modem chemical information environment Learn how to explore the scientific literature, how to use the information found in agreement with intellectual property laws, and learn about the current trends impacting chemists as creators of knowledge. Research skills in the Open Science Era CIVIL-608 Research Skills in the Open Science Era is a course designed to explore t
Fides ZenkTeaching & PhD PhD Students Hanrong Hu, Eugenio Stefano Gentile, Ece Naz Bilgiç, Nahuel Jonas Simonet, Yong-Qi Gao, Tekin Can Sobaci, Angel Lizandro Polanco Maldonado Courses Neuroscience foundations for engineers BIOENG-310 This overview course bridges computational expertise with neuroscience fundamentals, aimed at fosteringinterdisciplinary communication and collaboration for engineering-based neuroscience programs. Practical - Zenk Lab BIO-625 You will learn to prepare
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
Alexander MathisAlexander studied pure mathematics with a minor in logic and theory of science at the Ludwig Maximilians University in Munich. For his PhD also at LMU, he worked on optimal coding approaches to elucidate the properties of grid cells. As a postdoctoral fellow with Prof. Venkatesh N. Murthy at Harvard University and Prof. Matthias Bethge at Tuebingen AI, he decided to study olfactory behaviors such as odor-guided navigation, social behaviors and the cocktail party problem in mice. During this time, he increasingly got interested sensorimotor behaviors beyond olfaction and started working on proprioception, motor adaption, as well as computer vision tools for measuring animal behavior.
In his group, he is interested in elucidating how the brain gives rise to adaptive behavior. One of the major goals is to synthesize large datasets into computationally useful information. For those purposes, he develops algorithms and systems to analyze animal behavior (e.g. DeepLabCut), neural data, as well as creates experimentally testable computational models.
Yujia ZhangExpertise
Dropletronics: microscale droplet-based modular iontronics (e.g., batteries, diodes, transistors, memristors and circuits)Bioiontronics and bioelectronicsFunctional synthetic, cellular and hybrid tissuesBioengineering and human-machine interfaceAdvanced manufacturing of soft and living matter across multiple scales
2026 Masters Semester Project/Thesis, PhD and Postdoc Positions
Many opportunities exist in microengineering, bioengineering, materials science, microrobots, programming and AI; please
Mackenzie MathisCenter for NeuroprostheticsEPFL ELLIS Unit Faculty MemberCenter for Intelligent Systems
Stefana ParaschoTeaching & PhD PhD Students Jingwen Wang, Gabriel Vallat, Maxence Grangeot, Eleni Maria Skevaki, Wenqian Yang, Megi Sinani Courses Capitalizing on Uncertainty AR-809 SUMMER SCHOOL - Capitalizing on Uncertainty is a 6-day Summer school exploring uncertainty as a productive resource in design and fabrication through lectures, hands-on experiments, and the collaborative design and construction of a full-scale structure in a human-robot fabrication setting. Digital design and making: A criti
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
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
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 (
