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
Jonathan Yuelin DongTeaching & PhD PhD Students Zhiyuan Hu Past EPFL PhD Students as codirector Yan Liu
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.
Simone IadanzaTeaching & PhD Courses Nanophotonics MICRO-516 Students understand and apply the physics of the interaction of light with semiconductors. They understand the operating mechanism of scaled photonic devices such as photodetectors, LEDs and lasers, as well as challenges and opportunities relating to their integration and dimensional scaling.
Keivan Faghih NiresiExpertise
Computational sensing/imaging, Inverse problems, Signal processing, Graph neural networks, Domain adaptation.
Keivan is a PhD student at école Polytechnique Fédérale de Lausanne (EPFL). He joined the Intelligent Maintenance and Operations Systems (IMOS) Lab under the supervision of Prof. Olga Fink in February 2023.Prior to joining EPFL, he obtained his master's degree from the Institute of Communications Engineering, College of Electrical Engineering and Computer Science, National Tsing Hua Univer
Zheru QiuBefore joining LPQM, I graduated from University of Science and Technology of China with a bachelor's degree. In USTC, I actively worked in Prof. Zheng-tian Lu's research group and I mainly participated in the atomic magnetometer project led by Prof. Dong Sheng.
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
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•
Michail VlachosTeaching & PhD Courses Data science and machine learning MGT-502 Hands-on introduction to data science and machine learning. We explore recommender systems, generative AI, chatbots, graphs, as well as regression, classification, clustering, dimensionality reduction, text analytics, neural networks. The course consists of lectures and coding sessions using Python.
Gopal Narmada NaiduExpertise
Researcher with 8+ years of experience in computational physics and multiphysics modeling, focused on numerical simulation of light–matter interactions and photon propagation. Proficient in FEM, FDTD, and Monte Carlo methods to model energy conversion and optical behavior, with additional expertise in AI/ML techniques for model optimization and design exploration. Strong background in photonic devices, photo-thermal, thermo-optical effects, and nanostructure engineering. Adept at translating compl
Pasquale ScarlinoI obtained my master's degree in Physics at the University of Salento, Lecce (Italy) in February 2011. During 2006-2011, I have also been a student of Scuola Superiore ISUFI (SSI). SSI is one of six schools of excellence established in Italy to develop the intellectual capital in technological and social sciences. I conducted an external Master thesis project during an 8 months internship in the Quantum Transport Group at TU Delft, under the supervision of Prof. L.M.K. Vandersypen. There, I implemented the Quantum Point Contact Radio-Frequency Reflectometry technique, which allows increasing the single-shot electron spin readout bandwidth and is currently routinely used in the group.I obtained my Ph.D. degree in February 2016, in the Spin Qubits group of Prof. L.M.K. Vandersypen at the Kavli Institute of Nanoscience-Qutech (TU Delft). During my Ph.D. I have been leading the Si/SiGe spin qubits project, collaborating with the M. Eriksson Group at Wisconsin University. In parallel, I have been working on other different projects, in particular with GaAs depletion quantum dots, high impedance superconducting resonators, and surface acoustic wave resonators. I have been working as a Postdoc fellow in the group of Prof. A. Wallraff (Quantum Device Lab) at ETH Zurich. My main project, in collaboration with the group of Prof. K. Ensslin and Prof. T. Ihn, consisted in integrating semiconductor and superconductor technologies. Realizing a well-controlled interface between the semiconductor and superconductor-based quantum information technologies may allow harnessing the best of both device architectures, for example by providing an interface between strongly coupled charge state and high coherence spin states. Furthermore, it enables the possibility to explore light/matter hybridization in a class of solid-state systems and regimes that are new in the context of quantum optics.From June 2019 till September 2020, I have been a Senior Researcher at Microsoft Station Q Copenhagen and at the Center for Quantum Devices in Copenhagen, focusing on developing semiconductor-superconducting hybrid hardware for topologically protected quantum computation.Since October 2020, I am a tenure track Assistant Professor of Physics in the School of Basic Sciences at the EPFL where I founded the Hybrid Quantum Circuit (HQC) laboratory.
Manuel Guizar SicairosTeaching & PhD PhD Students Aknur Karabay, Pengju Sheng, Wenxuan Fang Courses Physical Optics and Advanced Imaging PHYS-715 This course gives an introduction to principles of Fourier and physical optics, numerical propagation, and sampling. On the second half the course covers topics of advanced imaging, including 3 external lecturers who are experts in application or development of advanced imaging techniques.
Christian André Clément LafforgueTeaching & PhD Courses Electrical engineering science & technology EE-106 This course introduces the fundamental laws of electricity and the methods for analyzing linear electrical circuits, consisting of resistors, capacitors and inductors. We will start with the Direct Current circuits and then switch to single-phase and three-phase Alternating Current circuits.
Alexander DittrichCurrent Work
My research interests are somewhere between neural networks with Hebbian plasticity, meta-reinforcement learning, and the control of rather unconventional soft robotic platforms like tensegrity robots.
Giuseppe CarleoGiuseppe Carleo is a computational quantum physicist, whose main focus is the development of advanced numerical algorithms tostudy challenging problems involving strongly interacting quantum systems.He is best known for the introduction of machine learning techniques to study both equilibrium and dynamical properties,based on a neural-network representations of quantum states, as well for the time-dependent variational Monte Carlo method.He earned a Ph.D. in Condensed Matter Theory from the International School for Advanced Studies (SISSA) in Italy in 2011.He held postdoctoral positions at the Institut d’Optique in France and ETH Zurich in Switzerland, where he alsoserved as a lecturer in computational quantum physics.In 2018, he joined the Flatiron Institute in New York City in 2018 at the Center for Computational Quantum Physics (CCQ), working as a Research Scientist and project leader, and also leading the development of the open-source project NetKet.Since September 2020 he is an assistant professor at EPFL, in Switzerland, leading the Computational Quantum Science Laboratory (CQSL).
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
