Computer Science Dept. Affiliate 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
This fall I am teaching a graduate Ai class on Real life Reinforcement Learning. Join us!
- Best paper award RLDM (2015)
- Office of Naval Research Young Investigator Award (YIP) (2015) (Press release)
- NSF CAREER award (2014)
- Best paper nominee CHI (2014)
- Best paper nominee EDM (2013)
- Microsoft Research Faculty Fellow (2012) (1 of 7 worldwide)
- Best paper nominee EDM (2012)
- Aug 2015: Delighted to be a co-PI on a NSF BIGDATA award with PI Zoran Popovic and co-PI Min Li on machine learning optimization for education!
- June 2015: Congratulations to Shayan Doroudi and Kenneth Holstein for being selected as PIER fellows!
- May 2015: Congratulations to Yun-En Liu on a successful defense!
- Dec 2014: Great to give 3 invited presentations at NIPS workshops
- Winter 2014: Enjoyed presenting "Learning to Improve Learning" as part of CMU's IdeasLab at the World Economic Forum in Davos
I am fortunate to get to work with a great set of individuals and I am currently working with
- Christoph Dann
- Shayan Doroudi
- Daniel Guo
- Kenneth Holstein
- Yun-En Liu (joint with Zoran Popovic, University of Washington)
- Travis Mandel (joint with Zoran Popovic, University of Washington)
- Rika Antonova
- Qi Guo
- (Dexter) Min Hyung Lee
- Joe Runde
- Li Zhou
If you're an undergraduate or graduate at CMU interested in helping us transform and scale personalized learning, or tackling new challenges in sequential
decision making under uncertainty, please get in touch!