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Welcome! I am a research scientist at Google DeepMind working closely with Andrew Zisserman. I recently completed my PhD in the Machine Learning Department at CMU, working with Alyosha Efros and Abhinav Gupta. I graduated from CMU in 2010 with a B.S. in computer science and cognitive science, with a minor in neural computation, completing an undergraduate thesis with Tai Sing Lee.

I'm interested in computer vision and all the learning problems that are associated with it. In particular, I'm interested self-supervised and unsupervised learning. In computer vision, the standard labels we use (e.g. bounding boxes, keypoint annotations) not only tend to be expensive to collect, but they also tend to be a poor approximation to what we actually know about images. Yet some types of labels come cheaply: for example, GPS tags, web text, and even raw image context. My work aims to show that these cues can provide roughly the same information as manually collected labels, and allow us to learn representations that are driven by the data, rather than by annotators.

Thanks to Google for a Fellowship supporting my PhD.