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.
Federico TerziTeaching & PhD Courses Music, politics and society I HUM-406 This course examines the presence of exotic musical characteristics (popular and folkloric) - in Europe and beyond - in art music (17th-20th centuries). It culminates in a group (or individual) research paper on a subject related to this theme. Music, politics and society II HUM-458 This course examines the presence of exotic musical characteristics (popular and folkloric) - in Europe and beyond - in art music (17th
Francesco RomanoExpertise
Gyrotrons, Non-Neutral Plasma, Electric Space Propulsion, Helicon Plasma Thrusters, Atmosphere-Breathing Electric Propulsion
Current Work
The TRapped Electrons eXperiment - T-REX
Born in Sassari and grew up in Udine, I studied Aerospace Engineering for Bachelor, Master in Italy and I've earned my Ph.D. in Germany. I also graduated in organ and organ composition at the conservatory in Italy. I Love space, science, music (piano, organ, classical, classic rock), endurance and uphill cycling, classic
Mackenzie MathisCenter for NeuroprostheticsEPFL ELLIS Unit Faculty MemberCenter for Intelligent Systems
Yanina Yurina ShkelTeaching & PhD PhD Students Serhat Emre Coban, Anuj Kumar Yadav, Cemre Çadir Courses Advanced probability and applications COM-417 In this course, various aspects of probability theory are considered. The first part covers the main theorems in the field (law of large numbers, central limit theorem), while the second part focuses on the theory of martingales and concentration inequalities. Signal processing COM-202 Signal processing theory and applications: discrete and cont
Ioannis RammosYannis Rammos is a postdoc at the EPFL Digital & Cognitive Musicology Lab and visiting piano faculty at European University Cyprus. An internationally active pianist and piano pedagogue trained in Russia, during the past two years he has been invited to deliver performances, masterclasses, and lectures at the Estonian Academy for Music & Theater, the Russian Institute for Art History, Conservatorium van Amsterdam, and the Aristotle University School of Music, among other venues. Formerly a researcher in music theory at the Sibelius Academy, he completed his doctoral studies in piano and music theory at the CUNY Graduate Center and New York University, graduating from the latter with a Ph.D. in classical performance. His latest peer-reviewed publications have appeared in
Music & Letters
,
Quodlibet
, and
Music Theory & Analysis
. His research spans Schenker studies, critical theory (especially of French poststructuralist origin), Russian music theory, and piano timbre studies. At EPFL he contributes to the Laboratory's overarching corpus initiative, focusing on the history of Western harmony and formalizations of Schenkerian tonal structures.
Georgios MoschidisTeaching & PhD PhD Students Abraham Gabriel Dorsaz Courses Analysis IV (for EL, GM, MX) MATH-207(c) This course serves as an introduction to the theory of complex analysis, Fourier series and Fourier transforms, the Laplace transform, with applications to the theory of ordinary and partial differential equations. These tools play an integral role in most branches of science and engineering. Differential geometry I - curves and surfaces MATH-213 This course serves as an intr
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.
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