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
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
Ernst HardyTeaching & PhD Courses Non-destructive methods for industry and research MSE-668 Basic knowledge ofthe classical non-destructive testing methods as they are used today in industrial applications and the advanced(mosily imaginé) technologies used for the analysis of materials and components in special applications. lt covers several material groups and various applications.
Annapaola ParrilliTeaching & PhD Courses Non-destructive methods for industry and research MSE-668 Basic knowledge ofthe classical non-destructive testing methods as they are used today in industrial applications and the advanced(mosily imaginé) technologies used for the analysis of materials and components in special applications. lt covers several material groups and various applications.
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•
Leonid MoninTeaching & PhD Courses Algebra III - rings and fields MATH-215 This is an introductory course in ring and field theory. Analysis I (English) MATH-101(en) We study the fundamental concepts of analysis, calculus and the integral of real-valued functions of a real variable. Topology III - Homology MATH-323 Homology is one of the most important tools to study topological spaces and it plays an important role in many fields of mathematics. The aim of this course is
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
Rajita Ramesh ChandakExpertise
Nonparametric estimation, statistical inference, theory of machine learning
Teaching & PhD Courses Nonparametric estimation and inference MATH-524 Nonparametric models are used to identify a wide range of relationships within data. This course gives a graduate-level overview of nonparametric statistical estimation and inference theory. Statistical inference MATH-562 Inference from the particular to the general based on probability models is central to the statistica
Pedro Correa FernandezPedro Correa Fernández is a Doctoral Candidate in Architecture at Columbia GSAPP. Before joining GSAPP, he was an adjunct professor at the Architecture School of Universidad Católica de Chile where he taught seminars and lectures on architecture history and related epistemological, aesthetic, and political issues. His current work examines the mediations between technical knowledge, artisanal crafts, and global industrial capitalism in early nineteenth-century Latin America.Pedro holds an architecture degre
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
Julie Nathalie S GheysenProfessionals experiences PhD student 2018–2022 Université Catholique de Louvain
Teaching & PhD Courses Materials MSE-171 Introduction course of material science applied to usual building materials, especially concrete and metals. Description of their fabrication, mechanical and thermal properties and use in construction. Mechanical behaviour of materials MSE-234 This course provides an introduction to the mechanical behaviour, the processing, the structure and life-cycle o
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
Gregor JotzuGregor Jotzu is heading the Dynamic Quantum Materials Laboratory (DQML) at EPFL. His research concerns the control of quantum materials using intense low-frequency laser pulses and the dynamics of order formation in strongly correlated quantum systems.After reading physics at the University of Oxford, he became the 2009/2010 Michael von Clemm Fellow at Harvard University. He received his doctorate from ETH Zurich, where he studied quantum magnetism and driving-induced order using ultracold atoms in optical
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
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.
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
Wenlong LiaoExpertise
deep learning, power system, renewable energy, data analysis
