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
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 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
Sophia BeckerExpertise
Computational and theoretical neuroscienceReinforcement learning
Stefana ParaschoTeaching & PhD PhD Students Jingwen Wang, Gabriel Vallat, Maxence Grangeot, Eleni Maria Skevaki, Wenqian Yang, Megi Sinani Courses Capitalizing on Uncertainty AR-809 SUMMER SCHOOL - Capitalizing on Uncertainty is a 6-day Summer school exploring uncertainty as a productive resource in design and fabrication through lectures, hands-on experiments, and the collaborative design and construction of a full-scale structure in a human-robot fabrication setting. Digital design and making: A criti
Mackenzie MathisCenter for NeuroprostheticsEPFL ELLIS Unit Faculty MemberCenter for Intelligent Systems
Andres Osorio SalazarExpertise
Robotics, advanced actuator design, soft actuators, sensor design, embedded systems, human-machine interface architecture, electronic-less control, mechanism design, additive and traditional manufacturing, industrial automation, process control, and fluid robotics.
Current Work
Smart Footwear for Diabetic Foot Care and Ulcer PreventionEvery 20 seconds, a person with diabetes has to face an amputation somewhere in the world. The main risk factor is high plantar pressure combined with foot nephropat
Icare SakrMaths and Science enthusiast from my young age, at 14 I decided to create my robot developing brand called RobotIcare and built several LEGO machines, which allowed me to earn experience in robotics.
Today, I strive to pursue my goal of understanding the human brain and developing platforms that allow brain enhancement using Brain-Computer Interface technologies.
Mohammad Ali ShaeriExpertise
Neural Engineering, Neural Signal Processing, Neural Decoding, Neural Prosthesis, Brain Machine Interface
