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 currently hold a joint position as a Research Scientist at Google Brain and Postdoctoral Fellow at UC Berkeley. I received my PhD from MIT, where I worked on Affective Computing and deep/reinforcement/machine learning. I have interned at DeepMind, Google Brain, and worked as an OpenAI Scholars mentor. I am currently on the faculty job market.

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Interests
  • Multi-Agent Learning and Coordination
  • Human-AI Interaction
  • Affective Computing
  • Reinforcement Learning
  • Machine Learning
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

  • 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.
  • 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