Computer Science Dept.
Affiliate faculty with the Machine Learning Dept.
Carnegie Mellon University
ebrunskill at cs dot cmu dot edu
My lab focuses on creating autonomous agents that learn
to interact with people, envisioning systems like self-optimizing tutors
that proactively improve their teaching as they interact with
more students. Accomplishing this requires new algorithmic and
theoretical advances in machine learning, optimal control and artificial
intelligence. I am particularly excited about the potential
of machine learning to transform the effectiveness of
online education and most of my lab's application work focuses
on education. I am also passionate about how information techology can
assist in challenges arising in low resource settings (ICTD) and
very interested in health applications.
I did my PhD at MIT and my postdoc at the University of California, Berkeley.
- Spring 2014: 2 ICML papers accepted and 1 EDM paper!
- Winter 2014: Yun-en Liu's CHI paper received an Honorable Mention!
- Winter 2014: Excited to be part of the CMU-Yahoo InMind project
- Winter 2014: Enjoyed presenting "Learning to Improve Learning" as part of CMU's IdeasLab at the World Economic Forum in Davos
- Winter 2014: Congratulations to Yun-en Liu on his CHI paper and Travis Mandel on his AAMAS paper!
- Fall 2013: Great workshops at NIPS! Particularly enjoyed sharing my & collaborators' work on transfer learning, machine learning & education, and modeling HIV patients
- Fall 2013: Paper with Mohammad Azer and Alessandro Lazaric ("Sequential Transfer in Multi-arm Bandit with Finite Set of Models") accepted to NIPS
- Summer 2013: Delighted that IES has funded me and co-PI Vincent Aleven (HCII) $1.5 million to work on "Use of Machine Learning to Adaptively Select Activity Types and
Enhance Student Learning with an Intelligent Tutoring System"
- Summer 2013: Yun-en Liu's EDM paper is nominated for best paper. Congratulations Yun-en!
- Summer 2013: Paper with Mohammad Azer and Alessandro Lazaric ("Regret Bounds for Reinforcement Learning with Policy Advice") accepted to ECML
- Spring 2013: Paper with Lihong Li on multi-task reinforcement learning accepted to UAI
- Spring 2013: Two papers accepted to Education Data Mining. Congratulations to Yun-en Liu and Anna Rafferty!
- Dec 2012: I gave a joint invited tutorial with Geoff Gordon on "Machine Learning for Student Learning" at NIPS.
- Fall 2012: I had a great time presenting my group's work as part of
CMU's IdeasLab at the World Economic Forum in Tianjin, China.
- Summer 2012: I received a Google Research Award. Thanks Google!
- Summer 2012: Paper on Incentive Decision Processes (with Sashank Reddi) accepted to UAI.
- Summer 2012: Jung In Lee and I had a paper nominated for best paper at the International Conference on Educational Data Mining. Congratulations to Jung In!
- Spring 2012: I'm delighted to have been selected as a
Microsoft Research Faculty Fellow.
- Spring 2012: I co-taught (with Professor Manuela Veloso) a new class on Artificial Intelligence for Health & Sustainability.
- Summer 2011: I co-organized a IJCAI workshop on Decision Making in Partially Observable, Uncertain Worlds