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Bio
Dr. Adrien Gaidon is a partner at Calibrate Ventures, where he leverages his extensive experience in AI and robotics to help startups solve ambitious real-world problems. Adrien is also a Technical Advisor in AI at Toyota Research Institute (TRI) and an Adjunct Professor of Computer Science at Stanford University, where he teaches and advises the next generation of Computer Vision talent.
Before joining Calibrate, Adrien served as Director of Machine Learning (ML) at TRI. As a researcher, engineer, manager, and executive, Adrien built and led teams working simultaneously on both cutting-edge research and large-scale practical applications, especially in safety-critical domains like automated driving. Adrien has a deep expertise in ML for Embodied Intelligence, with more than 100 patents and 100 highly cited publications at top AI venues like CVPR, ICRA, and NeurIPS.
At Calibrate, Adrien leverages his industry networks and deep technical expertise to fund and support market-ready deep-tech companies capitalizing on both artificial and human intelligence.
Before joining Calibrate, Adrien served as Director of Machine Learning (ML) at TRI. As a researcher, engineer, manager, and executive, Adrien built and led teams working simultaneously on both cutting-edge research and large-scale practical applications, especially in safety-critical domains like automated driving. Adrien has a deep expertise in ML for Embodied Intelligence, with more than 100 patents and 100 highly cited publications at top AI venues like CVPR, ICRA, and NeurIPS.
At Calibrate, Adrien leverages his industry networks and deep technical expertise to fund and support market-ready deep-tech companies capitalizing on both artificial and human intelligence.
Research Interests
Papers共 114 篇Author StatisticsCo-AuthorSimilar Experts
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CoRR (2024)
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arxiv(2024)
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CVPR 2023 (2023): 9213-9222
CLeaR (2023): 386-407
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arXiv (Cornell University)pp.381-392, (2023)
2023 IEEE/CVF International Conference on Computer Vision (ICCV) (2023): 9153-9164
2023 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR)pp.22836-22845, (2023)
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