Phillip Isola

Phillip Isola is the Class of 1948 Career Development 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.

Selected Publications

• Shen, W., Yang, G., Yu, A. C. L., Wong, J., Kaelbling, L. P., & Isola, P. (2023). Distilled feature fields enable Few-Shot Language-Guided manipulation. 7th Annual Conference on Robot Learning (CoRL). https://doi.org/10.48550/arxiv.2308.07931
• Baradad, M., Chen, C., Wulff, J., Wang, T., Feris, R., Torralba, A., & Isola, P. (2022). Procedural image programs for representation learning. 36th Conference on Neural Information Processing Systems (NeurIPS). https://doi.org/10.48550/arxiv.2211.16412
• Jahanian, A., Puig, X., Tian, Y., & Isola, P. (2022). Generative models as a data source for multiview representation learning. International Conference on Learning Representations (ICLR). https://openreview.net/pdf?id=qhAeZjs7dCL

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