PhD Student at CMU & Student Researcher at Google Brain
beysenba @cs.cmu.edu, @ben_eysenbach
Bio: I'm a PhD student in the Machine Learning Department at Carnegie Mellon University and a student researcher in Google Brain. I am co-advised by Ruslan Salakhutdinov and Sergey Levine. My PhD is supported by the National Science Foundation (GFRP) and the Hertz Fellowship. Previously, I was a Resident at Google Brain. I studied math and computer science at MIT.
Research summary: My research has focused on designing better RL algorithms.
- Data-driven control [1, 2]
- Safety and robustness [1, 2, 3]
- Unsupervised RL and skill learning [1, 2]
- Planning and inference [1, 2] ... and demonstrating that these algorithms work on real robots [1, 2]
Research opportunities: I am usually looking for students to help with research projects both during the semester and over the summer. If you are interested, please send me an email. I especially encourage students from underrepresented groups to reach out.
- We've released C-Learning, an RL algorithm for predicting and controlling the states an agent will visit in the future. C-learning seems to work better than Q-learning, and hindsight relabeling emerges automatically (it even suggests how to choose the optimal goal-sampling ratio!) [paper, website, code]
- Check out a recent blog post explaining a ``supervised learning'' perspective on RL, which is a unifying thread in a number of recent multi-task RL papers: [blog post]
- Our paper on hindsight relabeling and inverse RL was accepted as an Oral at NeurIPS! [paper]
- I was a guest on the TalkRL podcast: https://www.talkrl.com/episodes/ben-eysenbach
See Google Scholar for a complete and up-to-date list of publications.
Assorted Blog Posts
© 2021 Ben Eysenbach