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
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
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
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.
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
Mackenzie MathisCenter for NeuroprostheticsEPFL ELLIS Unit Faculty MemberCenter for Intelligent Systems
Benjamin Alexander Kellenberger2020–: Postdoctoral Researcher, EPFL, Sion, Switzerland2020: Postdoctoral researcher, Wageningen University, Netherlands2017–2020: PhD (cont'd); Wageningen University, Netherlands2016–2017: PhD; University of Zurich, Switzerland2009–2014: BSc. and MSc. in geography (remote sensing and GIS) and computer science; University of Zurich, Switzerland
Xavier Fernandez-Real GironaTeaching & PhD PhD Students Roberto Colombo Courses Optimal transport MATH-476 The first part is devoted to Monge and Kantorovitch problems, discussing the existence and the properties of the optimal plan. The second part introduces the Wasserstein distance on measures and develops applications of optimal transport to PDEs, functional/geometric inequalities, traffic models.
Elisabeth AgoritsasExpertise
=> See my personal homepage for more content https://eagoritsas.wordpress.com.Statistical physics of classical disordered systems, with focus on specific classes of models:disordered elastic interfaces and random manifolds,mesoscopic elasto-plastic models (spatially-resolved and effectively mean-field versions),mean-field description of structurally disordered systems (e.g. glasses) in infinite dimensions,continuous random perceptron model.1D Kardar-Parisi-Zhang equation and its encompassing unive 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
Lenka ZdeborováLenka Zdeborová is a Professor of Physics and of Computer Science in École Polytechnique Fédérale de Lausanne where she leads the Statistical Physics of Computation Laboratory. She received a PhD in physics from University Paris-Sud and from Charles University in Prague in 2008. She spent two years in the Los Alamos National Laboratory as the Director's Postdoctoral Fellow. Between 2010 and 2020 she was a researcher at CNRS working in the Institute of Theoretical Physics in CEA Saclay, France. In 2014, she was awarded the CNRS bronze medal, in 2016 Philippe Meyer prize in theoretical physics and an ERC Starting Grant, in 2018 the Irène Joliot-Curie prize, in 2021 the Gibbs lectureship of AMS. She is an editorial board member for Journal of Physics A, Physical Review E, Physical Review X, SIMODS, Machine Learning: Science and Technology, and Information and Inference. Lenka's expertise is in applications of concepts from statistical physics, such as advanced mean field methods, replica method and related message-passing algorithms, to problems in machine learning, signal processing, inference and optimization. She enjoys erasing the boundaries between theoretical physics, mathematics and computer science.
Lazar MilikicExpertise
LLMs (Large Language Models), NLP (Natural Language Processing), Automated Reasoning
Mission
My work focuses on developing robust methods for autoformalization and automated theorem proving using large language models. I aim to enhance the reasoning reliability of modern AI systems by reducing hallucinations, improving predictability, and integrating formal verification techniques and tools into LLM-based pipelines.
Before joining EDIC, I completed a Bachelor’s in Mathematics and Computer Science
Mohammad Ali ShaeriExpertise
Neural Engineering, Neural Signal Processing, Neural Decoding, Neural Prosthesis, Brain Machine Interface
Johannes HentschelJohannes Hentschel studied music education, music theory, and Romance studies in Freiburg i. Br., Lübeck, and Helsinki. Proficient as an accordionist, singer and conductor, he is a lecturer for music theory at music universities. In 2018, however, he suspended this activity for the Digital Humanities Doctoral Program at the Swiss Federal Insititute of Technology Lausanne (EPFL). Supervised by Prof. Dr. Martin Rohrmeier at the Digital and Cognitive Musicology Lab (DCML), Johannes is preparing a thesis on diachronic style change in music while deepening his knowledge in corpus building and metadata organization.
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.
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.
Gabriele CecchettiAfter being awarded an MPhil at the Centre for Music and Science (University of Cambridge), Gabriele Cecchetti joined the Digital and Cognitive Musicology Lab (EPFL) as a doctoral assistant in 2019. In Rome, his hometown, he previously graduated in physics (Università ‘La Sapienza’) and as a cellist (Conservatorio ‘S. Cecilia’). His research interests lie on a spectrum spanning from music analysis and performance to the mathematical and theoretical modelling of the cognitive underpinnings of the experience of music. For his master’s project, he focused on a small-scale information-theoretic model of tonal affinity based on psychoacoustic and neuroscientific insight. Within the ERC-funded project ‘Principles of Musical Structure Building’ he will engage with matching theoretical and computational approaches with empirical cognitive and psychological frameworks. He is also an experienced musician with a particular devotion to chamber music, and has been extensively involved in music teaching over several years of collaboration with the educational programs of the National Academy ‘S. Cecilia’ in Rome.
