John Co-Reyes

John Co-Reyes is a PhD student at UC Berkeley, conducting research on deep reinforcement learning under the guidance of Sergey Levine. His main focus is on developing versatile algorithms to empower machines in acquiring complex behaviors in areas such as robotics, computer vision, and NLP.

His research interests include learning latent dynamics models for model-based RL, meta-learning RL algorithms and optimizers, and integrating unsupervised objectives into open-world environments to facilitate the advancement of general intelligence. He has significant contributions as a 1st and 2nd author in renowned conferences like ICLR, ICML, NeurIPS, and CoRL.

John's educational background comprises a Doctor of Philosophy (PhD) in Artificial Intelligence from UC Berkeley, where he is currently pursuing his research. Prior to this, he completed a Bachelor of Science (BS) in Computer Science with a high GPA of 3.8 from the California Institute of Technology.

In terms of professional experience, John has served as a Research Scientist at Google, bringing his expertise in machine learning to the company's projects. He has also worked as a Machine Learning Consultant at Rebel Space Technologies and held positions such as Google Brain Research Intern, PHD Student at UC Berkeley, Research Intern at Clarifai, Algorithm Engineer Intern at Nervana Systems, and Undergraduate Researcher at Caltech.

Additionally, John has gained industry experience through roles like Software Development Engineer Intern at Amazon and Summer Undergraduate Research Fellow at Jet Propulsion Laboratory. His diverse background also includes serving as an EMT-B at Wilton Volunteer Ambulance Corps, an Intern and Researcher at Earthplace-The Nature Discovery Center, and a Martial Arts Instructor at Kempo Academy of Martial Arts.