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
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
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
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.
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
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
Anne-Florence Raphaëlle BitbolI was trained in physics, and always had a strong interest in biology. I am broadly interested in understanding biological phenomena in a quantitative way, through physical concepts and mathematical and computational tools. I investigate the relative impacts of optimization and historical contingency in biological evolution, both at the scale of protein sequences and at the scale of microbial populations.Here is my research group website.Curriculum vitae Here is my complete CV. Professional experience:Since
Sofia Charlotta OlhedeI am a professor of Statistics at EPFL. I did my PhD in Mathematics at Imperial College London, and graduated in 2003. I was an assistant professor (lecturer) at Imperial College London 2002-2006, and an associate professor (senior lecturer) 2006-2007. In 2007 I moved to University College London and became a full professor. I moved to EPFL in 2019, and in 2018 I became an Institute of Mathematical Statistics Fellow with citation “For seminal contributions to the theory and application of large and heteroge
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
Caglar GulcehreTeaching & PhD PhD Students Tim Ruben Davidson, Skander Moalla, Anja Surina, Xiuying Wei, Liangze Jiang, Mikhail Terekhov, Amin Mansouri, Justin Samuel Deschenaux, Yitao Xu Courses Training Large Language Models EE-628 This PhD-level course dives deep into the training of Large Language Models (LLMs), focusing on the complementary roles of datasets, pre-training and post training methodologies in shaping model performance and scalability.
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.
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.
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.
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.
Petter Harald EricsonPetter Ericson is a formal language and theoretical computing science expert, specifically focused on efficient graph grammars formalisms, who has joined the DCML as a Postdoctoral Researcher in 2019. He achieved his undergraduate degrees in Computing Science, as well as his PhD in the same subject, at Umeå University, investigating various topics within the general area of (parameterized) complexity theory, automata theory and formal languages, specifically looking at more complex structures such as graphs and trees. In particular, his work touched on applications in Natural Language Processing such as mildly context-sensitive syntax analysis and semantic modelling and processing.
An avid trombonist and amateur composer and arranger as well as a sometimes hacker and maker, his musical and research interests have previously intersected at the international Music Tech Fest events, where his presentations has garnered two hack camp wins, and a semi-regular place in the organising team.
