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
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
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
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
Andres Osorio SalazarExpertise
Robotics, advanced actuator design, soft actuators, sensor design, embedded systems, human-machine interface architecture, electronic-less control, mechanism design, additive and traditional manufacturing, industrial automation, process control, and fluid robotics.
Current Work
Smart Footwear for Diabetic Foot Care and Ulcer PreventionEvery 20 seconds, a person with diabetes has to face an amputation somewhere in the world. The main risk factor is high plantar pressure combined with foot nephropat
Simon HolzerHi, I am Simon Holzer. I received my B.Sc. and M.Sc. degrees in mechanical engineering with a focus on microtechnology from the Swiss Federal Institute of Technology Zurich (ETHZ) in 2020 and 2022, respectively. I am currently working towards Ph.D. in the Integrated Actuators Laboratory (LAI) at EPFL in Neuchâtel, Switzerland. My research interests lie in the field of soft robotics, artificial muscles, and biomechanics.
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•
Caglar GulcehreTeaching & PhD PhD Students Tim Ruben Davidson, Skander Moalla, Anja Surina, Xiuying Wei, Liangze Jiang, Mikhail Terekhov, Amin Mansouri, Justin Samuel Deschenaux, Yitao Xu Courses Training Large Language Models EE-628 This PhD-level course dives deep into the training of Large Language Models (LLMs), focusing on the complementary roles of datasets, pre-training and post training methodologies in shaping model performance and scalability.
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
Tim Ruben DavidsonExpertise
deep generative models; agentic systems; synthetic data; representation learning
Mission
I study how deep generative models can be used to power agentic systems and generate useful synthetic data
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
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.
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
Chenghao XuEducation Bachelor of Engineering | Mechnical Engineering 2016 – 2020 Southern University of Science and Technology, China Master of Science | Robotics 2020 – 2023 Delft University of Technology, Netherlands
