Natasha Jaques recently finished her PhD at MIT under Rosalind Picard, where she focused on improving the social and affective intelligence of deep/reinforcement/machine learning. She is now continuing to work on multi-agent social reinforcement learning as a Research Scientist at Google Brain and Berkeley, working with Sergey Levine and Doug Eck. Her work has received an honourable mention for best paper at ICML 2019, a best paper award at the NeurIPS ML for Healthcare workshop and was part of the team that received Best Demo at NeurIPS 2016. 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.