Emma Brunskill

Emma Brunskill is an Assistant Professor in the Department of Computer Science at Carnegie Mellon University, with affiliations in Machine Learning. Her research advances interactive machine learning to enhance human potential, focusing on education and health applications.

• Academic Rank: Assistant Professor
• Current University: Carnegie Mellon University
• Future Position: Will join Stanford University's CS Department in March 2017

Her work spans theoretical reinforcement learning, self-optimizing tutoring systems, and scalable solutions for education and healthcare. She leads a lab testing AI-driven pedagogy in classrooms.

Her 15 most recent publications (2015-2016) focus on reinforcement learning theory, Bayesian clustering, contextual bandits, POMDP planning, and educational AI. Keywords include Machine Learning, Human-Computer Interaction, and Computational Sustainability.

Scientific Awards:

• Best paper award RLDM (2015)
• Office of Naval Research Young Investigator Award (2015)
• NSF CAREER award (2014)
• Best paper nominee CHI (2014)
• Best paper nominee EDM (2013)
• Microsoft Research Faculty Fellow (2012)
• Best paper nominee EDM (2012)

She mentors multiple PhD and Masters students and co-led NSF BIGDATA grant Machine Learning Optimization for Education with Zoran Popovic. Her teaching includes Real Life Reinforcement Learning (Fall 2015) and course organization at CMU.