Konstantinos KarapiperisKostas Karapiperis is an Assistant Professor at EPFL directing the Data-Driven Mechanics Laboratory (LMD). His research lies at the intersection of mechanics, multiscale modeling, and data science, with applications ranging from geomaterials to structural materials. Prior to EPFL, he worked as a Postdoctoral Researcher and Lecturer at the Department of Mechanical and Process Engineering of ETH Zürich, supported by a Marie Sklodowska-Curie Fellowship. He holds a PhD in Applied Mechanics and a Minor in Applie
Zepeng ZhangZepeng is a PhD student at École Polytechnique Fédérale de Lausanne (EPFL). He works in the Intelligent Maintenance and Operations Systems (IMOS) Lab under the supervision of Prof. Olga Fink. Previously, He received his master’s degree at ShanghaiTech University and B.Eng. degree from Wuhan University (WHU). During his studies, he have visited Télécom Paris, Institut Polytechnique de Paris (IP Paris), Peking University (PKU), and City University of HongKong (CityU) as a research intern. His current research
Umut AltuntasExpertise
fracture mechanics, experimental solid mechanics, fatigue, additive manufacturing, polymer science, soft materials
Education Aerospace Engineering | 2021 – 2024 Middle East Technical University
Sangwoo KimSangwoo Kim is set to join EPFL as a Tenure Track Assistant Professor in September 2023. Prior to his appointment at EPFL, he served as a postdoctoral fellow in the Department of Mechanical Engineering at the University of California, Santa Barbara. He earned his graduate degree in Theoretical and Applied Mechanics from the University of Illinois at Urbana-Champaign, where his research delved into the relationships between statistics, geometry, and mechanical states in cellular matters. Currently, his research focus on fundamental understanding of biological and living systems, as well as the study of soft and active matter employing principles from mechanics and physics. His research interests encompass embryonic development, tissue morphogenesis, structure and mechanics of soft materials, inherent structure of amorphous materials, and non-equilibrium dynamics of active matter.
Brayden Graham MyersTeaching & PhD Courses General physics : mechanics (English) PHYS-101(en) Students will learn the principles of mechanics to enable a better understanding of physical phenomena, such as the kinematics and dyamics of point masses and solid bodies. Students will acquire the capacity to quantitatively analyze these effects with the appropriate theoretical tools.
Geovani RizkExpertise
Distributed Machine Learning, Robustness, Safety, Optimization, Multi-Agent, Bandits in Graphs
I am a postdoctoral researcher at école Polytechnique Fédérale de Lausanne since 2022, where I work with Rachid Guerraoui on robustness of distributed machine learning algorithms. From 2018 to 2022, I completed my Ph.D. in computer science at Université Paris Dauphine-PSL on multi-agent bandits in graphs under the supervision of Yann Chevaleyre, Rida Laraki, Igor Colin, and Albert Thomas.Pre-prints Over
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
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
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
Charlotte Cäcilie Gertrud BunneCharlotte Bunne is an assistant professor at EPFL in the School of Computer and Communication Sciences (IC) and School of Life Sciences (SV). She is part of the Swiss Institute for Experimental Cancer Research (ISREC) and the EPFL AI Center. Before, she was a PostDoc at Genentech and Stanford working with Aviv Regev and Jure Leskovec and completed a PhD in Computer Science at ETH Zurich working with Andreas Krause and Marco Cuturi. During her graduate studies, she was a visiting researcher at the Broad Inst
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•
Antonio TintiCurrent Work
Marie Skłodowska-Curie Global Fellow @ LSMO EPFL, Project HydroMOF
Professionals experiences Tenure-Track Assistant Professor (RTT) Faculty position at the Departiment of Mechanical and Aerospace Engineering of Sapienza University 2026–2026 Sapienza Università di RomaScientist Postdoctoral Scientist @ LSMO, EPFL, working with Prof. B. Smit 2024–2026 EPFLAssistant Professor without Tenure (RTD-A) Fixed-Time Faculty Position 2021–2024 Sapienza University of RomePostdoctoral Fellow Postdoctoral
Mengjie ZhaoMengjie Zhao holds degrees in Computational Mechanics (MSc) with honors track and in Engineering Science (BSc) from the Technical University of Munich (TUM).
From the early years of her studies, Mengjie was fascinated by the modeling of multiphysics and multiscale systems. As a student research assistant at TUM and research intern at International Centre for Numerical Methods in Engineering (CIMNE), she gained a solid understanding of both the theoretical and algorithmic fundamentals as well as a wide range of applications. Through the BGCE project with the Elitenetzwerk Bayern (ENB), which dealt with the mesh sensitivity prediction with a deep neural network, she realized that leveraging data could bring physical modeling far beyond the current computational limits. Later, in her master's thesis in cooperation with Siemens, she turned to the reduced-order modeling with enforced physical invariants, which showed better accuracy and generality.
In her Ph.D., she would like to step towards a further combination of deductive research (modeling and simulation) and inductive (data-driven) research by embedding physics into machine learning.
Adriano MeleI am a control engineer and plasma scientist at the Swiss Plasma Center of the École Polytechnique Fédérale de Lausanne.I am also Research Topic Coordinator in the EUROfusion Tokamak Exploitation WorkPackage, for the Research Topic 04: Physics-based machine generic systems for an integrated control of plasma discharge, and an Associate Editor in the Franklin Open journal.In 2022-2023, I have been an Assistant Professor in Automatic Control at the University of Tuscia, Viterbo.Before that, from 2019 to 2021,
Wenlong LiaoExpertise
deep learning, power system, renewable energy, data analysis
Andrea CavalliTeaching & PhD PhD Students Alessia Ghidini Courses Drug Discovery CH-630 The course gives an overview of drug discovery. Computational methods in drug design and discovery, including methods for free energy and residence time, drug-target interactions, pharmacodynamics, pharmacokinetics, and drug delivery,biophysical methods, interaction including ITC, SPR, MST, and NMR.
