Hi! I’m Bradley Emi. I’m an M.S. student in Computer Science with specialization in Artificial Intelligence at Stanford University. I do research in the Stanford Vision and Learning Lab (SVL) advised by Silvio Savarese and Amir R. Zamir. I graduated from Stanford with a B.S. in Physics in 2018.
I’m interested in reinforcement learning with a focus on real-world perception. My recent work focuses on transferring knowledge from large computer vision models to active tasks for robotics in the Gibson environment.
Starting in Fall 2019, I’m excited to be joining the Tesla Autopilot team as a machine learning scientist!
In-the-loop perception for reinforcement learning in real environments that trains fast and generalizes immediately to new unseen spaces.PDF
A program that can automatically recognize and parse the structure of hand-drawn chemical molecules using machine learning and classical computer vision, even generalizing to molecules unseen in training.PDF
I contributed an image processing pipeline for raw Hubble Space Telescope data and multi-wavelength galaxy models to GalSim, a galaxy image simulator which includes simulation of the effects of dark energy and dark matter.PDF
Machine learning algorithms for perception and motion planning for autonomous vehicles at Uber.