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 FinkEnseignement et PhD Doctorant·es actuel·les Han Sun, Leandro Von Krannichfeldt, Keivan Faghih Niresi, Zepeng Zhang, Vinay Sharma, Chenghao Xu, Raffael Pascal Theiler, Kevin Antonio Steiner, Sergei Garmaev, Amaury Wei A dirigé les thèses EPFL de Ismail Nejjar, Mengjie Zhao Cours Data Science for infrastructure condition monitoring CIVIL-332 Le cours couvrira les étapes pertinentes de la surveillance de l'état des infrastructures basée sur les données: l'acquisition des données, en passant p
Zoë HolmesEnseignement et PhD Doctorant·es actuel·les Ricard Puig, Sacha Lerch, Reyhaneh Aghaei Saem, Shao Hen Chiew, Weijie Xiong, Marc Sanz Drudis, Mehrad Sahebi, Manuel Rudolph Cours Quantum information theory PHYS-550 Après avoir revu les bases de la théorie quantique du point de vue de la théorie de l'information, nous couvrirons des sujets plus avancés en théorie de l'information quantique tels que les mesures de l'information quantique et la compréhension des états, canaux et mesures quantiqu
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
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•
Ricard Puig I VallsExpertise
I'm interested on Variational Quantum Algorithms, Quantum Simulation and Quantum Metrology and Sensing. Overall in general I love studying how we can exploit quantum resources to surpass the classical limits.
Expertise
I'm interested on Variational Quantum Algorithms, Quantum Simulation and Quantum Metrology and Sensing. Overall in general I love studying how we can exploit quantum resources to surpass the classical limits.
I obtained my BSc in Physics in 2022 from the Autonomous University of Bar
Manuel Sebastian RudolphExpertise
Computational quantum physicsQuantum algorithmsQuantum machine learningGenerative modeling
Manuel is a PhD Candidate at EPFL in the group of Prof. Zoë Holmes, where he focuses on the numerical simulation of quantum computers. Together with his collaborators, he studies which properties make quantum circuits easy or hard to simulate classically, and how efficient classical simulability is connected to the barren plateau phenomenon. Manuel develops high-performance quantum simulation software and is
Vittorio ErbaEnseignement et PhD Cours Statistical physics of computation PHYS-512 Les étudiants comprennent les outils de la physique statistique des systèmes désordonnés et les appliquent pour étudier des problèmes d'informatique et de statistiques en théorie des graphes, en optimisation discrète, ainsi qu'en inférence et en apprentissage automatique.
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