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
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
Michail VlachosEnseignement et PhD Cours Data science and machine learning MGT-502 Introduction pratique à la science des données et à l'apprentissage automatique. Nous abordons les systèmes de recommandation, l'IA générative, les chatbots, les graphes, ainsi que la régression, la classification, l'analyse de texte et les réseaux neuronaux. Programmation en Python.
Alexander DittrichCurrent Work
My research interests are somewhere between neural networks with Hebbian plasticity, meta-reinforcement learning, and the control of rather unconventional soft robotic platforms like tensegrity robots.
Sanggyu ChongSanggyu "Raymond" Chong obtained his BS, MS and PhD degrees in Chemical and Biomolecular Engineering from Korea Advanced Institute of Science and Technology (KAIST), where he primarily focused on the computational design of metal-organic frameworks for applications ranging from gas storage to functional electronics. In March 2022, Sanggyu joined COSMO as a postdoctoral researcher, and he is currently investigating the robustness of local and/or component-wise predictions made by atomistic machine learning m
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.
Jiancheng YangI am a 4th-year PhD student in the Department of Electronic Engineering, Shanghai Jiao Tong University, advised by Prof. Bingbing Ni. I received BEng and MEng degree in the Department of Automation from the same university. Enrolled in a double master degree program, I spent 2 years in France with an Engineer degree. I was a visiting research fellow in Visual Computing Group at Harvard University. I am now visiting EPFL CVLAB, working with Prof. Pascal Fua.I focus on medical image analysis, 3D computer vision and trustworthy machine learning, with a clinical emphasis on lung cancer and thoracic diseases. I have (co-)first-authored more than 10 papers on top-tier journals / conferences, e.g., Cancer Research, CVPR, MICCAI and NeurIPS. I was a reviewer for more than 10 prestigious venues, a top-ranking participant for several AI competitions, and the lead organizer for MICCAI 2020 RibFrac Challenge.Updated on April, 2021.
Mohammad Ali ShaeriExpertise
Neural Engineering, Neural Signal Processing, Neural Decoding, Neural Prosthesis, Brain Machine Interface
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