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Théau Peronnin is a distinguished Research Scientist at Google DeepMind, based in Paris. His work is centered on advancing the frontiers of artificial intelligence, with a particular focus on machine learning, computer vision, and generative models. He holds a PhD in Computer Science from Université Grenoble Alpes, where his research concentrated on learning visual representations with limited or no supervision, conducted at Inria. Before joining Google DeepMind, Théau has been involved in various research roles, contributing to the development of novel algorithms and models that push the boundaries of AI capabilities. He is passionate about creating intelligent systems that can perceive, understand, and interact with the complex world around us, often at the intersection of vision and language.
Théau Peronnin's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Completed doctoral research at Université Grenoble Alpes (conducted at Inria) focusing on 'Learning visual representations with limited or no supervision,' contributing significant insights and methodologies to unsupervised and self-supervised learning in computer vision.
Contributes to cutting-edge AI research projects at one of the world's leading AI labs, focusing on areas like generative models, multimodal learning, and advanced computer vision techniques. His work aims to develop more capable and general AI systems.
Authored and co-authored numerous research papers published in prestigious AI and machine learning conferences and journals such as NeurIPS, ICML, CVPR, and ICLR, showcasing impactful contributions to the field.
Involved in research that has pushed the state-of-the-art in generative modeling, including developing models capable of synthesizing high-fidelity images and understanding complex visual data.
Ecole polytechnique - Year 2012
Ecole normale supérieure - Year 2015
Lycée Condorcet - Year 2010
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Alice & Bob is a French deep-tech company developing fault-tolerant quantum computers to help industries and researchers solve some of the world's most challenging problems. They specialize in 'cat qubits,' a type of superconducting qubit designed to be passively protected against bit-flip errors, one of the two main types of errors that plague quantum systems. Their goal is to build a universal, error-corrected quantum computer significantly sooner than competitors by simplifying the hardware requirements.
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