Emma Brunskill is an assistant professor in the computer science department at Stanford University where she leads the AI for Human Impact (@ai4hi) group. Her work focuses on reinforcement learning in high-stakes scenarios-how can an agent learn from experience to make good decisions when experience is costly or risky, such as in educational software, health care decision making, robotics or people-facing applications.  She was previously on the faculty at Carnegie Mellon University. She is the recipient of multiple early faculty career awards, including from the National Science Foundation, the Office of Naval Research, and Microsoft Research. Her group has received several best research paper nominations and awards in top machine learning for education conferences and AI conferences.

In this talk, Emma explores how her research helps to design algorithms that will enable technology to teach.