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.
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
Mackenzie MathisCenter for NeuroprostheticsEPFL ELLIS Unit Faculty MemberCenter for Intelligent Systems
Ayberk OzkirliDr. Ayberk Ozkirli is a vision neuroscientist whose research investigates how spatiotemporal context influences visual perception.He completed his PhD in Neuroscience at the Laboratory of Psychophysics at EPFL in 2025, under the supervision of Prof. Michael Herzog and Prof. David Pascucci. He holds an M.Sc. in Bioengineering from EPFL (Switzerland) and a B.Sc. in Electrical and Electronics Engineering from Bilkent University (Turkey).His expertise spans neuroimaging, statistics, experimental design, neural
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
Gioele La MannoTeaching & PhD PhD Students Albert Dominguez Mantes, Xinyi Huang, Laura Lapeña Gil, Alessandro Valente, Luca Fusar Bassini, Hao-An Hsiung, Alireza Gargoorimotlagh, Morgane Alice Storey, Rosan Martine Hans, María Cristina Loureiro Casalderrey, Lada Polyakova Past EPFL PhD Students Alex Russell Lederer, Irina Khven Past EPFL PhD Students as codirector Alexandre Coudray, Alex Russell Lederer, Halima Hannah Emilie Schede, Irina Khven Courses Biological data science I: statistical learning BIOENG-210
Alireza ModirshanechiI am a computer science Ph.D. student in the Laboratory of Computational Neuroscience at EPFL where I work on computational models of learning and decision-making in the brain - under the supervision of Prof. Wulfram Gerstner. My main track of research focuses on (i) mathematical definitions of surprise and novelty, (ii) their influence on human behavior, and (iii) their manifestation in physiological measurements. I use statistical inference, information theory, and reinforcement learning to develop theoretical models which I test against behavioral and physiological data. I have worked with EEG, MEG, fMRI, and single neuron recordings.
Prior to joining EPFL, I received my B.Sc. in Electrical Engineering from the Sharif University of Technology, Tehran. During the last two years of my study, I did a few research projects in the Augmented Intelligence Research Lab (AIR Lab) under the supervision of Prof. Hamid Aghajan. My projects were mainly on (i) studying biomarkers of surprise in EEG signals, (ii) decoding surprise using these biomarkers, and (iii) fMRI-based classification of visual and auditory stimuli.
You can find my random scientific notes and educational articles here in my Medium account, and more information about me on my personal website.
Erick Jorge Canales RodriguezExpertise
My research interests lie at the intersection between physics, mathematical modelling, computer science, and neuroscience. My research contributions focus on developing novel imaging techniques to study the brain tissues using different Magnetic Resonance Imaging (MRI) modalities and applying these computational methods to brain imaging data to study various brain disorders.
Expertise
My research interests lie at the intersection between physics, mathematical modelling, computer science, and neuro
