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 masterclasses, performances, and lectures at the Anton Bruckner Privatuniversität für Musik, the Estonian Academy for Music & Theater, the Russian Institute for Art History, and Conservatorium van Amsterdam, 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 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.
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
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
Federico TerziEnseignement et PhD Cours Musique, politique, société I HUM-406 Ce cours propose d'étudier la présence de particularités musicales exotiques (populaires et folkloriques) - en Europe et au-delà - dans la musique classique (XVIIe-XXe siècles). Il débouche sur la rédaction d'un travail de recherche en groupe (ou individuel) sur un sujet lié à cette thématique. Musique, politique, société II HUM-458 Ce cours propose d'étudier la présence de particularités musicales exotiques (pop
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
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
Georgios MoschidisEnseignement et PhD Doctorant·es actuel·les Abraham Gabriel Dorsaz Cours Analysis IV (for EL, GM, MX) MATH-207(c) Ce cours est une introduction à la théorie de l'analyse complexe, aux séries et transformées de Fourier, à la transformée de Laplace, avec des applications à la théorie des équations différentielles ordinaires et partielles. Differential geometry I - curves and surfaces MATH-213 Ce cours constitue une introduction à la géométrie différentielle classique, qui ét
Yanina Yurina ShkelEnseignement et PhD Doctorant·es actuel·les Serhat Emre Coban, Anuj Kumar Yadav, Cemre Çadir Cours Advanced probability and applications COM-417 Dans ce cours, différents aspects de la théorie des probabilités sont abordés. La première partie est dévolue à ses principaux théorèmes (loi des grands nombres, théorème central limite), tandis que la seconde partie porte sur la théorie des martingales et inégalités de concentration. Signal processing COM-202 Théorie et appli.du t
Shashwat ShrivastavaI am a Ph.D. student at EPFL, advised by Dr. Mirjana Stojilović. I am broadly interested in FPGA architecture and Computer-Aided Design. My research is focused on reducing the compile time for FPGAs by incorporating architectural enhancements and rethinking CAD algorithms.
Han SunExpertise
Deep Learning, Computer Vision, Domain Adaptation, Generative Modeling
Open Projects:
Test-Time Domain Adaptation for Anomaly Detection: SiROP link for detailed information
Han obtained her master's degree in Geomatic from the Federal Institute of Technology in Zürich (ETHZ). Before joining IMOS Lab - EPFL, she focused on computer vision with a particular interest in domain adaptation & style adaptation. During her Ph.D. study, she will explore more in the field of domain adaptation with its appli
Simon Elias BibriExpertise
• Sustainable cities• Smarter eco-cities• Sustainable smart cities• Artificial Intelligence of Things (AIoT) • Generative Artificial Intelligence of Things (GAIoT)• Foundation Models (FMs) • Quantum Generative Artificial Intelligence (QGAI)• Urban Digital Twins (UDTs)• Urban Brain (UB) • Smart Circular Metabolism• Urban planning and design• Environmental sustainability and climate resilience• Sustainable smart energy• Sustainable smart transportation• Sustainable smart waste and water management•
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
Mackenzie MathisCenter for NeuroprostheticsEPFL ELLIS Unit Faculty MemberCenter for Intelligent Systems
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.
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
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.
Martin Nicolas EveraertExpertise
Computer Vision, Generative Models, Deep Learning, Computational aesthetics, Diffusion Model
Martin Nicolas Everaert is a PhD student in the Image and Visual Representation Lab (IVRL) at EPFL, under the guidance of Prof. Dr. Sabine Süsstrunk and Dr. Radhakrishna Achanta. He received an MSc degree in Computer Science from EPFL in 2021. Prior to that, he received a Master's degree from CentraleSupélec (Ingénieur diplômé de l'école supérieure d'électricité) in 2021 and a Bachelor's degree in fundamen
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.
