Faculty

Natasha Jaques is an Assistant Professor at the University of Washington Paul G. Allen School of Computer Science & Engineering, where she leads the Social RL Lab. She is also a Senior Research Scientist at Google DeepMind.

During her Ph.D. at MIT, Jaques 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). In the multi-agent space, she developed techniques for improving coordination through the optimization of social influence.

Jaques interned at DeepMind, Google Brain, and was an OpenAI Scholars Mentor. She was subsequently a Visiting Postdoctoral Scholar at UC Berkeley, in Sergey Levine’s group, and a Senior Research Scientist at Google Brain, where she built novel methods for adversarial environment generation to improve the robustness of RL agents. Her 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. Her work has been featured in Science Magazine, MIT Technology Review, Quartz, IEEE Spectrum, Boston Magazine, and on CBC radio, among others. Jaques earned a Master’s degree from the University of British Columbia, and undergraduate degrees in Computer Science and Psychology from the University of Regina.