Hello there! I'm Jacob Buckman, currently an intern at MILA. Usually, I'm a PhD student at Johns Hopkins advised by Jason Eisner.

My primary research area is deep reinforcement learning. I'm especially interested in working towards sample-efficiency. My current work focuses on finite-sample guarantees and latent-space modeling.

I graduated from Carnegie Mellon University in 2017 with a Bachelor's in computer science and a Master's in Language Technologies, advised by Graham Neubig . From 2017-2018, I was a Google AI Resident in San Francisco.



Website template stolen with love from Desh.