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
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
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.
Valerio ZerbiDr. Valerio Zerbi is a pioneer of preclinical magnetic resonance functional neuroimaging. At his lab at EPFL, Valerio and his team use functional MRI recordings in rodents in combination with neural modulation and computational approaches to study the mechanisms that link cellular activity to large-scale network (dys)function. His long-term ambition is to advance the development of personalised strategies based on imaging and artificial intelligence, for the diagnosis and prognosis of developmental brain disorders. Valerio is the recipient of the ETH Postdoctoral (2014), the Swiss National Science Foundation AMBIZIONE
(2017) and ECCELLENZA (2021) fellowships.
Sophia BeckerExpertise
Computational and theoretical neuroscienceReinforcement learning
Angela Ingrid RentonExpertise
Visual perceptionAttentionPredictionDecision-makingM/EEGClosed-loop neuroimagingOpen & reproducible science
Mission
Angela Renton completed her PhD in 2022 at under the supervision of Prof. Jason Mattingley, at The University of Queensland, Australia. Her PhD investigated the development of novel neurofeedback and closed-loop research methods to causally investigate the neural mechanisms of visual perception. As a postdoctoral research fellow, she has expanded on this work, working on real-time ne
Maria PavlouEnseignement et PhD Doctorant·es actuel·les Yong-Qi Gao Cours Methods: omics in biomedical research BIOENG-519 Les méthodologies à haut débit, appelées "Omiques", permettent de caractériser la complexité et la dynamique de tout système biologique. Ce cours fournira une description générale des méthodes liées au domaine des "Omiques", suivie de rotations pratiques dans les plateformes participantes.
Olga FinkEnseignement et PhD Doctorant·es actuel·les Han Sun, Leandro Von Krannichfeldt, Keivan Faghih Niresi, Zepeng Zhang, Vinay Sharma, Chenghao Xu, Raffael Pascal Theiler, Kevin Antonio Steiner, Sergei Garmaev, Amaury Wei A dirigé les thèses EPFL de Ismail Nejjar, Mengjie Zhao Cours Data Science for infrastructure condition monitoring CIVIL-332 Le cours couvrira les étapes pertinentes de la surveillance de l'état des infrastructures basée sur les données: l'acquisition des données, en passant p
Pasquale Davide SchiavoneEnseignement et PhD Cours Design technologies for integrated systems CS-472 La synthèse hardware est le processus de transformation - itérativement raffiné, détaillé et optimisé - d'une représentation faite en langage de description matérielle en un circuit. Ce cours présente les algorithmes, outils et méthodes de la compilation matérielle et de la synthèse logique.
Yujia ZhangEnseignement et PhD Doctorant·es actuel·les Yuyan Su, Shulang Shen, Jiaqi Liu Cours Advanced microfabrication practicals MICRO-373 Ce TP permet une formation approfondie sur les méthodes avancées de micro et nanofabrication dans un environnement de salle blanche pour des applications sélectionnées, d'acquérir des connaissances plus approfondies sur les processus MEMS/NEMS, de travailler dans un petit groupe avec des doctorants/ MOOC: Micro and Nanofabrication (MEMS) - Fall MICRO-
Mohammad Ali ShaeriExpertise
Neural Engineering, Neural Signal Processing, Neural Decoding, Neural Prosthesis, Brain Machine Interface
