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    John Co-Reyes

    Research Scientist at Google Brain

    John D. Co-Reyes is a research scientist at Google Brain, specializing in deep reinforcement learning and meta-learning.1 He completed his PhD at Berkeley AI Research Lab (BAIR) under the supervision of Sergey Levine, focusing on deep reinforcement learning and robotics.1 Prior to his doctoral studies, he obtained his B.S. from Caltech, where he worked on computer vision with Yisong Yue and Pietro Perona.1

    Co-Reyes's research interests include:

    1. Deep reinforcement learning
    2. Meta-learning
    3. Robotics
    4. Computer vision
    5. Representation learning
    6. Natural language processing

    His long-term goal is to contribute to the development of general AI and use it to accelerate research in other fields.1 He is particularly interested in combining deep learning with reinforcement learning to solve complex decision-making problems.1

    Co-Reyes has published several research papers at prestigious conferences such as ICLR, ICML, NeurIPS, and CoRL.2 Some of his notable works include:

    1. "Guiding Policies with Language via Meta-Learning" (ICLR 2019)
    2. "Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings" (ICML 2018)
    3. "EX2: Exploration with Exemplar Models for Deep Reinforcement Learning" (NeurIPS 2017)

    In addition to his academic pursuits, Co-Reyes has gained industry experience through internships at companies like Google Brain, Clarifai, and Nervana Systems (acquired by Intel).2

    Highlights

    ‪John D Co-Reyes‬ - ‪Google Scholar‬

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    John Co-Reyes
    John Co-Reyes, photo 1
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    Location

    San Francisco, California, United States