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
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
Mackenzie MathisCenter for NeuroprostheticsEPFL ELLIS Unit Faculty MemberCenter for Intelligent Systems
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.
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
Virginia LangVirginia started in the medical research field as a Coordinator of Research at the Clinical Research Unit Kennedy Institute of Johns Hopkins Medical Center. She was responsible for the initiation, coordination, and management and/or analysis of research projects in the Clinical Research Unit. These projects were funded by various Federal Government Agencies. Subsequent to Johns Hopkins Medical Center, Virginia entered the field of Human Factors through the doctoral program at SUNY Binghamton. Virginia held a fellowship at the Aeromedical Research Laboratory of the United States Air Force at Wright-Patterson AFB, Dayton, Ohio and a fellowship at NASA. Her research dealt with cognitive factors that differentially affect the characteristics of visual displays. Applications of this research are directly related to various medical devices and software applications providing Medical Device Human Factors by HirLan clients with 30 years of Human Factors experience. In addition, Virginia has extensive experience in the areas of product design, Customer Centered Participatory Design processes, and product lifecycle management. She is also known in the Human Computer Interaction and Usability Communities for her innovative techniques for collecting and incorporating user/customer feedback throughout the product lifecycle. In July 2014, Virginia founded and established the HirLan Institute of Human Factors with labs in Carlsbad, California and a Consortium arrangement in London, UK. HirLan supports Top Ten pharma/medical device companies, as well as, start-ups with consulting and testing services. These services are in conjunction with their clients’ FDA 510(k) and CE mark applications. Virginia holds a PhD in Cognitive-Experimental Psychology from SUNY Binghamton, and a Master of Science (ABT) in Applied Technology, Systems Science from SUNY Binghamton.
Sophia BeckerExpertise
Computational and theoretical neuroscienceReinforcement learning
Xavier Fernandez-Real GironaEnseignement et PhD Doctorant·es actuel·les Roberto Colombo Cours Optimal transport MATH-476 La 1er partie est consacrée aux problèmes de Monge et de Kantorovitch, discutant de l'existence et des propriétés du plan optimal. La 2ème partie introduit la distance de Wasserstein sur les mesures et développe des applications de transport optimal aux EDP, des inégalités fonctionnelles/géométrique
Steffen Alexander HerffSteffen graduated in Psychology at the Heinrich-Heine University Duesseldorf in Germany before going on to complete his PhD at the MARCS Institute for Brain, Behaviour, and Development focusing on 'Memory for Melody' in 2017, under the supervision of Prof. Roger Dean and Dr. Kirk Olsen.After his PhD, Steffen secured a DAAD-UA grant to conduct the "Noisy Ear" project in Germany, exploring context effects of background noise on memory before accepting a position at the Agency for Science, Technology and Research in Singapore, where he worked on Statistical Learning and memory paradigms in the auditory domain.Steffen's research is situated at the intersection between Memory, Music, and Neuroscience. His diverse interests and background have made him an integral part of many inter-disciplinary projects. These projects range from fundamental memory, learning, and perception research, over social negotiation between musical co-performers and the creation of new compositional tools, to non-invasive and invasive brain imaging in musical rhythm perception as well as brain stimulation to modulate memory encoding. Steffen strongly believes that inter-disciplinary research is the key to tackle complex, multi-facetted research questions.
Tanja Christina Käser JacoberTanja Käser is an assistant professor at the EPFL School of Computer and Communication Sciences (IC) and head of the D-VET laboratory. Her research lies at the intersection of machine learning, data mining, and education. She is particularly interested in creating accurate models of human behavior and learning.Prior to joining EPFL, Tanja Käser was a senior data scientist with the Swiss Data Science Center at ETH Zurich. Before that, she was a postdoctoral researcher with the AAALab at the Graduate School of Education of Stanford University.
Tanja Käser received her PhD degree from the Computer Science Department of ETH Zurich. In her dissertation, completed at the Computer Graphics Laboratory, she focused on user modeling and data mining in education, which was honored with the Fritz Kutter Award 2015.
Mohammad Ali ShaeriExpertise
Neural Engineering, Neural Signal Processing, Neural Decoding, Neural Prosthesis, Brain Machine Interface
