Phillip Isola
I am an associate professor in EECS at MIT studying computer vision, machine learning, and AI. Previously, I spent a year as a visiting research scientist at OpenAI, and before that I was a postdoctoral scholar with Alyosha Efros in the EECS department at UC Berkeley. I completed my Ph.D. in Brain & Cognitive Sciences at MIT, under the supervision of Ted Adelson, where I also frequently worked with Aude Oliva. I received my undergraduate degree in Computer Science from Yale, where I got my start on research working with Brian Scholl. A longer bio is here. ▸ Deep representation learning: What kinds of representations do deep nets learn? Why are these representations effective, and how are they limited? Representative projects: Platonic Representation Hypothesis, Low-rank bias, Understanding contrastive learning ▸ Generative intelligence: How can we use generative models as mental simulation engines, supporting learning, inference, and control? Representative projects: Learning from mod