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
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
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
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
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
Yoan Désiré DuhooTeaching & PhD Courses Integrative structural biology for Life sciences BIO-643 Hands-on course in Biomolecular Integrative Structural Biology by SV experts in the field of X-ray crystallography, cryo-Electron Microscopy, Bio-NMR and protein modeling tools. No previous knowledge in Structural Biology or Bioinformatics is required. Recombinant protein expression in animal cells for appli-cations in medicine and structural biology BIO-701 Cultivated animal cells are important
Lénaïc ChizatTeaching & PhD PhD Students Javier Esteban Maass Martinez Past EPFL PhD Students Guillaume Yitian Wang Courses Computational optimal transport MATH-528 Computational aspects of measure transportation, from classical optimal transport to modern denoising diffusion models. Topics in machine learning MATH-520 Mathematical analysis of modern supervised machine learning techniques, with an emphasis on the mathematics of artificial neural networks.
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.
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