Emma Brunskill
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Emma Patricia Brunskill is an American computer scientist. Her research combines machine learning with human–computer interaction by studying the effects of AI systems in human-centered applications including educational software and healthcare, and the theory of reinforcement learning in situations where mistakes impose high risks or costs. She is an associate professor of computer science at Stanford University, where she also holds a courtesy appointment in the Stanford Graduate School of Education and is an affiliate of the King Center on Global Development.[1]
Brunskill grew up in Seattle and Edmonds, Washington, and entered the University of Washington at age 15.[2] She graduated magna cum laude in 2000, with a bachelor's degree in computer engineering and physics.[3] A Rhodes Scholarship took her to Magdalen College, Oxford in England,[2] where she received a master's degree in neuroscience in 2002.[3] After a summer working in Rwanda,[2] she became a graduate student of computer science at the Massachusetts Institute of Technology, where she completed her Ph.D. in 2009.[3] Her doctoral dissertation, Compact parametric models for efficient sequential decision making in high-dimensional, uncertain domains, was supervised by Nicholas Roy.[4]
After working as an NSF Postdoctoral Research Fellow at the University of California, Berkeley, she joined Carnegie Mellon University (CMU) in 2011 as an assistant professor of computer science.[3] She moved from CMU to Stanford University in 2017.[5]
