Google Research

Natasha Jaques


Natasha Jaques holds a joint position as a Research Scientist at Google Brain and post-doc at UC Berkeley. Her research focuses on social reinforcement learning---developing multi-agent RL algorithms that can improve single-agent learning, generalization, coordination, and human-AI collaboration. Natasha received her PhD from MIT, where she worked on Affective Computing and deep/reinforcement/machine learning. Her work has received the best demo award at NeurIPS 2016, best paper at the NeurIPS workshops on ML for Healthcare and Cooperative AI, and an honourable mention for best paper at ICML 2019. She has interned at DeepMind, Google Brain, and is an OpenAI Scholars mentor. Her work has been featured in Quartz, the MIT Technology Review, Boston Magazine, and on CBC radio. Natasha earned her Masters degree from the University of British Columbia, and undergraduate degrees in Computer Science and Psychology from the University of Regina. See all publications at:

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