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
Virginia CarnevaliExpertise
Theoretical condensed matter physics: theory and simulations of structural, electronic, magnetic and optical properties (Quantum ESPRESSO), ab-initio molecular dynamics (CP2K), and Kinetic Monte Carlo codes; automate Quantum ESPRESSO workflows and high-throughput calculations (AFLOWÏ€); generation of tight-binding hamiltonians, transport properties, and data analysis (PAOFLOW).Materials for photovoltaic: Pb- and Sn-based organic perovskites; investigation and improvement of the HTL-ETL interaction
Myrto LimniosTeaching & PhD Courses Empirical processes MATH-522 We learn how to control the nonasymptotic and random behavior of collections of estimators, when indexed by classes of functions/sets. Examples range from prototypical estimators used by statisticians, to nonparametric models used in machine learning. Regression methods MATH-408 General graduate course on regression methods
Giovanna LaniExpertise
Theory development within many-body perturbation theory, time-dependent density functional theory and density-functional theory for problems pertaining to condensed matter physics and quantum chemistry
Expertise
Theory development within many-body perturbation theory, time-dependent density functional theory and density-functional theory for problems pertaining to condensed matter physics and quantum chemistry
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.
Sayan BiswasExpertise
Decentralized Machine Learning and Federated Learning focusing on Privacy, Fairness, and Personalization; Secure and Trustworthy Distributed Systems; Differential Privacy; Location Privacy.
Sayan Biswas (CV) is a Postdoctoral Researcher in the Scalable Computing Systems (SaCS) lab at EPFL, Switzerland, led by Prof. Anne-Marie Kermarrec. He completed his PhD in Computer Science at INRIA and école Polytechnique in France, under the supervision of Prof. Catuscia Palamidessi. Prior to that, Sayan stud
Francesco ArmillottaExpertise
Surface Science, Scanning Tunneling Microscopy, Desorption Spectroscopy, Heterogeneous Catalysis, Sum Frequency Generation Spectroscopy
I am presently a Postdoc in the Laboratory of Nanostructures at Surfaces (LSN) group, interested in the catalytic properties of surface-confined (sub)nano-structures. Education PhD | 2019 – 2023 University of Trieste
Teaching & PhD Courses Solid state physics PHYS-337 This lecture gives an introduction to Solid State Physics. We
Joelyn de LimaExpertise
Education ResearchPedagogical Professional DevelopmentInformal EducationAcademic communities
Joelyn de Lima is a scientist, educational developer, and researcher whose work bridges the natural sciences, higher education, and inclusive practice. Originally trained in the biological sciences, her early research focused on students’ conceptual and mechanistic understanding of evolution. She later transitioned into discipline-based education research and pedagogical development, bringing together scie
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