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
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•
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
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
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
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
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
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
Jonathan SchneiderTeaching & 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.
Angela SteinauerSince 2022: Head of the Laboratory of Biomolecular Engineering and Nanomedicine (LIBN), EPFL (Switzerland)2019-2021: MSCA Postdoctoral Fellow at ETHZ (Switzerland)2018: Ph.D. in Chemical Biology from Yale University (USA)2007-2012: B.Sc. & M.Sc. in Chemistry from University of Zurich (Switzerland)
Teaching & PhD PhD Students Diogo Miguel De Abreu Viegas, Georges Barnikol, Oliver Dennis, Andrea Elizabeth Melgar Aguilar, Paula Oeser, Manutsawee Thanaburakorn Courses Advanced general chemistry I CH
Markus JeschekTeaching & PhD PhD Students Ricardo Javier Farrera Muro, Clemens Felix Hausmann, Nikolas Seidel, Nicolas Alexander Jaenisch, Charlotte Desczyk, Izabella Maja Pomykalska Courses Chemical biology CH-313 Chemical Biology is an interdisciplinary field using chemical principles and techniques to analyse and manipulate biological systems. It relies on small-molecule chemicals to gain an in-depth understanding of biology, and provides new tools and products ranging from basic research to therapeu
Vladislav SlamaExpertise
Atomistic modeling of the biological pigment protein complexes consisting of molecular dynamics simulations (AMBER), computing ground and excited state properties of molecules and molecular aggregates including the effects of the environment (Gaussian, PyScf) and simulating excitation dynamics and optical spectra using quantum master equation approaches (Quantarhei).
Expertise
Atomistic modeling of the biological pigment protein complexes consisting of molecular dynamics simulations (AMBER), compu
Han SunExpertise
Deep Learning, Computer Vision, Domain Adaptation, Generative Modeling
Open Projects:
Test-Time Domain Adaptation for Anomaly Detection: SiROP link for detailed information
Han obtained her master's degree in Geomatic from the Federal Institute of Technology in Zürich (ETHZ). Before joining IMOS Lab - EPFL, she focused on computer vision with a particular interest in domain adaptation & style adaptation. During her Ph.D. study, she will explore more in the field of domain adaptation with its appli
Zepeng ZhangZepeng is a PhD student at École Polytechnique Fédérale de Lausanne (EPFL). He works in the Intelligent Maintenance and Operations Systems (IMOS) Lab under the supervision of Prof. Olga Fink. Previously, He received his master’s degree at ShanghaiTech University and B.Eng. degree from Wuhan University (WHU). During his studies, he have visited Télécom Paris, Institut Polytechnique de Paris (IP Paris), Peking University (PKU), and City University of HongKong (CityU) as a research intern. His current research
Sayan BiswasExpertise
Decentralized Machine Learning and Federated Learning focusing on Privacy, Fairness, and Personalization; Secure and Trustworthy Distributed Systems; Differential Privacy; Location Privacy.
Sayan Biswas (CV) is a Postdoctoral Researcher in the Scalable Computing Systems (SaCS) lab at EPFL, Switzerland, led by Prof. Anne-Marie Kermarrec. He completed his PhD in Computer Science at INRIA and école Polytechnique in France, under the supervision of Prof. Catuscia Palamidessi. Prior to that, Sayan stud
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
