Natasha Jaques

Natasha Jaques

Assistant Professor, University of Washington

Senior Research Scientist, Google DeepMind

Social learning helps humans and animals rapidly adapt to new circumstances, and drives the emergence of complex learned behaviors. My research is focused on Social Reinforcement Learning—developing algorithms that combine insights from social learning and multi-agent training to improve AI agents’ learning, generalization, coordination, and human-AI interaction.

I am an Assistant Professor at the University of Washington Paul G. Allen School of Computer Science & Engineering, where I lead the Social RL Lab. I am also a Senior Research Scientist at Google DeepMind. If you are interested in joining my lab as a PhD student, check out our contact page for more information.

During my PhD at MIT, I developed techniques for fine-tuning language models with RL and learning from human feedback which were later built on by OpenAI’s series of work on Reinforcement Learning from Human Feedback (RLHF) [1,2,3]. In the multi-agent space, I developed techniques for improving coordination through the optimization of social influence. I interned at DeepMind, Google Brain, and was an OpenAI Scholars Mentor. I was subsequently a Visiting Postdoctoral Scholar at UC Berkeley, in Sergey Levine’s group, and a Senior Research Scientist at Google Brain, where I built novel methods for adversarial environment generation to improve the robustness of RL agents. My work has received various awards, including Best Demo at NeurIPS, an honourable mention for Best Paper at ICML, and the Outstanding PhD Dissertation Award from the Association for the Advancement of Affective Computing. My work has been featured in Science Magazine, MIT Technology Review, Quartz, IEEE Spectrum, Boston Magazine, and on CBC radio, among others. I earned a Master's degree from the University of British Columbia, and undergraduate degrees in Computer Science and Psychology from the University of Regina.

Download my CV.

Education
  • PhD in the Media Lab, 2019

    Massachusetts Institute of Technology

  • MSc in Computer Science, 2014

    University of British Columbia

  • BSc in Computer Science, 2012

    University of Regina

  • BA in Psychology, 2012

    University of Regina

Selected Awards

Selected Press

  • Degrees Magazine. Cataldo, S. (2021, November 19). The sky’s the limit.
  • Science. Hutson, M. (2021, January 19). Who needs a teacher? Artificial intelligence designs lesson plans for itself.
  • IEEE Spectrum. Hutson, M. (2019, June 17). DeepMind Teaches AI Teamwork.
  • MIT Technology Review. Hao, K. (2019, June 20). Here are 10 ways AI could help fight climate change.
  • National Geographic. Snow, J. (2019, July 18). How artificial intelligence can tackle climate change.
  • Quartz. Gershgorn, D. (2018, February 16). Google is building AI to make humans smile.
  • MIT Technology Review. Knight, W. (2016, November 30). AI songsmith cranks out surprisingly catchy tunes.
  • Boston Magazine. Annear, S. (2015, January 5). Website tracks your happiness to remind you life’s not so bad.
  • CBC radio. Brace, S. (2015, January 5). Regina woman develops smile app at MIT.

Publications

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Tackling Climate Change with Machine Learning
This paper comprehensively surveys the ways in which machine learning could be usefully deployed in the fight against climate change. From smart grids to disaster management, we identify high impact problems and outline how machine learning can be employed to address them.

Featured Talks

Research Communities