Phillip Isola
Assistant Professor of Electrical Engineering and Computer Science at MIT Professional Education
Schools
- Sloan School of Management
- MIT Professional Education
Links
Biography
MIT Professional Education
Phillip Isola is an assistant professor in the MIT Department of Electrical Engineering and Computer Science. He received a bachelor’s degree in computer science from Yale University and a PhD in brain and cognitive sciences from MIT. Prof. Isola studies visual intelligence from the perspective of both minds and machines. He received a National Science Foundation (NSF) graduate fellowship as well as an NSF postdoctoral fellowship.
Phillip Isola is an assistant professor in MIT’s Department of Electrical Engineering and Computer Science and an investigator in the Computer Science and Artificial Intelligence Laboratory. His work focuses on why we represent the world the way we do, and how we can replicate these abilities in machines. Before coming to MIT, he was a visiting research scientist at OpenAI. He earned a PhD in brain and cognitive sciences at MIT and spent two years as a postdoc at the University of California, Berkeley.
Publications
- Tian, Y., Krishnan, D., Isola, P. (2020). Contrastive Representation Distillation. The International Conference on Learning Representations.
- Jahanian, A., Chai, L., Isola, P. (2020). On the “steerability” of generative adversarial networks. The International Conference on Learning Representations (ICLR).
- Pathak, D., Lu, C., Darrell, T., Isola, P., Efros, A. A. (2019). Learning to Control Self-Assembling Morphologies: A Study of Generalization via Modularity. Thirty-third Conference on Neural Information Processing Systems (NeurIPS).
- Yen-Chen, L., Bauza, M., Isola, P. (2019). Experience-embedded Visual Foresight. 3rd Annual Conference on Robot Learning (CoRL).
Videos
MIT EI Seminar - Phillip Isola - Emergent Intelligence: getting more out of agents than you bake in
Phillip Isola -- When and Why Does Contrastive Learing Work?
ICLR 2020 Social: Generative ML and Generalization
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