Vittorio ErbaTeaching & PhD Courses Statistical physics of computation PHYS-512 The students understand tools from the statistical physics of disordered systems, and apply them to study computational and statistical problems in graph theory, discrete optimisation, inference and machine learning.
Andrew James SontaExpertise
Human-building interaction, building energy, occupant behavior, sustainable design and planning, walkability, network analysis, machine learning, urban informatics, social systems.
Andrew Sonta is a tenure track assistant professor of sustainable civil engineering at EPFL. He directs the ETHOS Lab: Engineering and Technology for Human Oriented Sustainability. ETHOS is an interdisciplinary research group focused on using data-driven and computational tools to create interventions in the built envir
Gioele La MannoTeaching & PhD PhD Students Albert Dominguez Mantes, Xinyi Huang, Laura Lapeña Gil, Alessandro Valente, Luca Fusar Bassini, Hao-An Hsiung, Alireza Gargoorimotlagh, Morgane Alice Storey, Rosan Martine Hans, María Cristina Loureiro Casalderrey, Lada Polyakova Past EPFL PhD Students Alex Russell Lederer, Irina Khven Past EPFL PhD Students as codirector Alexandre Coudray, Alex Russell Lederer, Halima Hannah Emilie Schede, Irina Khven Courses Biological data science I: statistical learning BIOENG-210
Yujia ZhangExpertise
Dropletronics: microscale droplet-based modular iontronics (e.g., batteries, diodes, transistors, memristors and circuits)Bioiontronics and bioelectronicsFunctional synthetic, cellular and hybrid tissuesBioengineering and human-machine interfaceAdvanced manufacturing of soft and living matter across multiple scales
2026 Masters Semester Project/Thesis, PhD and Postdoc Positions
Many opportunities exist in microengineering, bioengineering, materials science, microrobots, programming and AI; please
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
Ehsan PajouheshgarExpertise
Computer Vision, Computer Graphics, Complex Systems, Machine Learning
Education Bachelor of Science | Major: Computer EngineeringMinor: Mathematics 2015 – 2020 Sharif University of Technology Computer Science | 2020 – 2025 EPFL Directed by Sabine Süsstrunk
Awards Teaching Assistance Excellence Award EPFL 2023 Best Student Paper Award From ALife 2024 Conference ALife 2024 Conference 2024 Best Paper Award From SIGGRAPH 2022 Conference ACM
Lénaïc ChizatTeaching & PhD PhD Students Javier Esteban Maass Martinez Past EPFL PhD Students Guillaume Yitian Wang Courses Computational optimal transport MATH-528 Computational aspects of measure transportation, from classical optimal transport to modern denoising diffusion models. Topics in machine learning MATH-520 Mathematical analysis of modern supervised machine learning techniques, with an emphasis on the mathematics of artificial neural networks.
Emma Elizabeth TolleyI studied the universe at the smallest scales at the Large Hadron Collider, now we're getting ready to study it at the largest scales with the Square Kilometer Array. My research focuses on developing high-performance computing and new data science techniques to image and analyse the radio sky.
Teaching & PhD PhD Students Markus Johan Bredberg, Ashutosh Kumar Mishra Past EPFL PhD Students as codirector Shreyam Parth Krishna Courses General physics : mechanics (english flipped classroom) PHYS-101
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.
