Computer Scientist | Jacob Beck
Description: Jacob Beck: Machine Teacher. Human Learner. University of Oxford. Formerly: Brown University, Microsoft Research, Adobe, Lyft.
I'm a DPhil (PhD) candidate at the University of Oxford supervised by Shimon Whiteson , funded by the Oxford-Google DeepMind Doctoral Scholarship, and studying deep reinforcement learning (RL). My main research area is meta-RL. (For an introduction, see this interview where I explain meta-RL!) I've worked on hypernetworks in meta-RL, bias-variance trade-offs in meta-gradients, and the consistency of meta-RL algorithms – in addition to a survey of meta-RL . Previously, I did my MS and BS at Brown Univ
At Brown University, I published research with the self-driving car lab, took many graduate seminars on ML, and was a TA for deep learning. During my master's degree I was advised by Michael Littman. My research focused on human feedback, imitation learning, multi-agent game theory. Some of our work gained publi city . Some other projects included: an RL agent that learns skills in Minecraft using emotion detection as feedback, a GAN that can reconstruct images of faces with up to 80% of the pixels missin
In industry, I worked at Microsoft, Lyft, and Adobe, in addition to several smaller companies. I completed a pre-doc at Microsoft Research with Katja Hofmann on long-term memory in RL. We published this work at ICLR 2020. At DeepScale, acquired by Tesla, I worked on perception for autonomous vehicles, developing novel methods for instance segmentation. At Lyft I designed a framework for solving sequential decision making problems with MDP's, including writing a special case solver for an MDP specific to aut
Computer Scientist | Jacob Beck