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About me
I am an assistant 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.
Research Group
Our group studies how to make artificial intelligence more like natural intelligence. We are especially interested in intelligence that is embodied, emergent, and general-purpose, all of which are properties that we see in humans and animals.Topics we currently focus on include representation learning, generative modeling, and multiagent systems. We also enjoy eclectic applications on top of these systems, often in vision and graphics, and also study the misuse of these systems, especially toward spreading misinformation.
The lab is part of the broader Embodied Intelligence and Visual Computing research communities at MIT.
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PhD Students Yen-Chen Lin (with Alberto Rodriguez) Caroline Chan (with Fredo Durand) Lucy Chai Yonglong Tian (with Josh Tenenbaum) Tongzhou Wang (with Antonio Torralba) Joseph Suarez Minyoung (Jacob) Huh (with Pulkit Agrawal) Hyojin Bahng (with Pulkit Agrawal) |
MEng Students Toru Lin Kenny Derek |
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Postdocs Swami Sankaranarayanan (with Antonio Torralba) |
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Affiliates and Collaborators Ali Jahanian, Evan Shelhamer, Alex Andonian, Kexin Yi, Xavier Puig, Shuang Li, David Bau, Jonas Wulff, Chuang Gan, Sabrina Osmany |
Former Members and Visitors Kevin Frans (UROP 2018-2020), Yilun Du (UROP 2019), Zhongxia Yan (Rotation 2019) |
Courses
6.819/6.869: Advances in Computer Vision (Spring 2021)6.036: Introduction to Machine Learning (Fall 2020)
6.882: Embodied Intelligence (Spring 2020)
6.819/6.869: Advances in Computer Vision (Fall 2019)
6.882: Embodied Intelligence (Spring 2019)
6.819/6.869: Advances in Computer Vision (Fall 2018)
Papers
| 2021 | |
| Explaining in Style: Training a GAN to explain a classifier in StyleSpace Oran Lang, Yossi Gandelsman, Michal Yarom, Yoav Wald, Gal Elidan, Avinatan Hassidim, William T. Freeman, Phillip Isola, Amir Globerson, Michal Irani, Inbar Mosseri arXiv 2021. [Paper][Website] | |
| Curious Representation Learning for Embodied Intelligence Yilun Du, Chuang Gan, Phillip Isola arXiv 2021. [Paper][Website][Code] | |
| Ensembling with Deep Generative Views Lucy Chai, Jun-Yan Zhu, Eli Shechtman, Phillip Isola, Richard Zhang CVPR 2021. [Paper][Website][Code][Colab] | |
| The Low-Rank Simplicity Bias in Deep Networks Minyoung Huh, Hossein Mobahi, Richard Zhang, Brian Cheung, Pulkit Agrawal, Phillip Isola arXiv 2021. [Paper][Website][Code] | |
| Using latent space regression to analyze and leverage compositionality in GANs Lucy Chai, Jonas Wulff, Phillip Isola ICLR 2021. [Paper][Website][Code][Demo (Colab)] | |
| 2020 | |
| iNeRF: Inverting Neural Radiance Fields for Pose Estimation Lin Yen-Chen, Pete Florence, Jonathan T. Barron, Alberto Rodriguez, Phillip Isola, Tsung-Yi Lin arXiv 2020. [Paper][Website] | |
| Noisy Agents: Self-supervised Exploration by Predicting Auditory Events Chuang Gan, Xiaoyu Chen, Phillip Isola, Antonio Torralba, Joshua B. Tenenbaum arXiv 2020. [Paper][Website] | |
| What makes for good views for contrastive learning? Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, Phillip Isola NeurIPS 2020. [Paper][Website][Code][Blog] | |
| Supervised Contrastive Learning Prannay Khosla*, Piotr Teterwak*, Chen Wang, Aaron Sarna, Yonglong Tian, Phillip Isola, Aaron Maschinot, Ce Liu, Dilip Krishnan NeurIPS 2020. [Paper][Code] | |
| What makes fake images detectable? Understanding properties that generalize Lucy Chai, David Bau, Ser-Nam Lim, Phillip Isola ECCV 2020. [Paper][Website][Code] | |
| Rethinking Few-Shot Image Classification: A Good Embedding Is All You Need? Yonglong Tian*, Yue Wang*, Dilip Krishnan, Josh Tenenbaum, Phillip Isola ECCV 2020. [Paper][Website][Code] | |
| Contrastive Multiview Coding Yonglong Tian, Dilip Krishnan, Phillip Isola ECCV 2020. [Paper][Website][Code] | |
| Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere Tongzhou Wang, Phillip Isola ICML 2020. [Paper][Website][Code] | |
| Neural MMO v1.3: A Massively Multiagent Game Environment for Training and Evaluating Neural Networks Joseph Suarez, Yilun Du, Igor Mordatch, Phillip Isola AAMAS Extended Abstract 2020. [Extended abstract][arXiv paper][Code] | |
| Learning to See before Learning to Act: Visual Pre-training for Manipulation Lin Yen-Chen, Andy Zeng, Shuran Song, Phillip Isola, Tsung-Yi Lin ICRA 2020. [Paper][Website][Code][Video][Blog] | |
| Contrastive Representation Distillation Yonglong Tian, Dilip Krishnan, Phillip Isola ICLR 2020. [Paper][Website][Code] | |
| On the "steerability" of generative adversarial networks Ali Jahanian*, Lucy Chai*, Phillip Isola ICLR 2020. [Paper][Website][Code] | |
2019 | |
| Neural MMO: A Massively Multiagent Game Environment for Training and Evaluating Intelligent Agents Joseph Suarez, Yilun Du, Phillip Isola, Igor Mordatch arXiv 2019. [Paper][Blog][Code] | |
| Learning to Control Self-Assembling Morphologies: A Study of Generalization via Modularity Deepak Pathak*, Chris Lu*, Trevor Darrell, Phillip Isola, Alexei A. Efros NeurIPS 2019. Winner of Virtual Creatures Competition at GECCO 2019 (link) [Paper][Website][Code] | |
| GANalyze: Toward Visual Definitions of Cognitive Image Properties Lore Goetschalckx*, Alex Andonian, Aude Oliva, Phillip Isola ICCV 2019. [Paper][Website][Code] | |
| InGAN: Capturing and Remapping the "DNA" of a Natural Image Assaf Shocher, Shai Bagon, Phillip Isola, Michal Irani ICCV 2019 (oral). [Paper][Website][Code] | |
| Experience-embedded Visual Foresight Lin Yen-Chen, Maria Bauza, Phillip Isola CoRL 2019. [Paper][Website][Code] | |
| Omnipush: accurate, diverse, real-world dataset of pushing dynamics with RGBD images Maria Bauza, Ferran Alet, Yen-Chen Lin, Tomas Lozano-Perez, Leslie P. Kaelbling, Phillip Isola, Alberto Rodriguez IROS 2019. [Paper][Website] | |
2018 | |
| Evolved Policy Gradients Rein Houthooft, Richard Y. Chen, Phillip Isola, Bradly C. Stadie, Filip Wolski, Jonathan Ho, Pieter Abbeel NeurIPS 2018. [Paper][Blog][Code] | |
| CyCADA: Cycle-Consistent Adversarial Domain Adaptation Judy Hoffman, Eric Tzeng, Taesung Park, Jun-Yan Zhu, Phillip Isola, Kate Saenko, Alexei A. Efros, Trevor Darrell ICML 2018. [Paper] | |
| Memorable words are monogamous: The role of synonymy and homonymy in word recognition memory Kyle Mahowald*, Phillip Isola*, Evelina Fedorenko, Edward Gibson, Aude Oliva PsyArXiv 2018. [Paper] | |
| The Unreasonable Effectiveness of Deep Features as a Perceptual Metric Richard Zhang, Phillip Isola, Alexei A. Efros, Eli Schechtman, Oliver Wang CVPR 2018. [Paper][Website][Code] | |
| What You Sketch Is What You Get: 3D Sketching using Multi-View Deep Volumetric Prediction Johanna Delanoy, Adrien Bousseau, Mathieu Aubry, Phillip Isola, Alexei A. Efros I3D 2018. [Paper][Video] | |
2017 | |
| Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks Jun-Yan Zhu*, Taesung Park*, Phillip Isola, Alexei A. Efros ICCV 2017. [Paper][Website][Code] | |
| Combining Self-Supervised Learning and Imitation for Vision-Based Rope Manipulation Ashvin Nair, Pulkit Agrawal, Dian Chen, Phillip Isola, Pieter Abbeel, Jitendra Malik, Sergey Levine ICRA 2017. [Paper][Website][Video] | |
| Richard Zhang*, Jun-Yan Zhu*, Phillip Isola, Xinyang Geng, Angela S. Lin, Tianhe Yu, Alexei A. Efros Real-Time User-Guided Image Colorization with Learned Deep Priors SIGGRAPH 2017. [Paper][Website][Code][Video] | |
| Ali Jahanian, Phillip Isola, Donglai Wei Mining Visual Evolution in 21 Years of Web Design CHI Extended Abstract, 2017. [Paper] | |
| Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, Alexei A. Efros Image-to-Image Translation with Conditional Adversarial Networks CVPR, 2017. [Paper][Website][Code][Demo] | |
| Richard Zhang, Phillip Isola, Alexei A. Efros Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction CVPR, 2017. [Paper][Website][Code] | |
2016 | |
| Richard Zhang, Phillip Isola, Alexei A. Efros Colorful Image Colorization European Conference on Computer Vision (ECCV), 2016 (oral). [Paper][Website][Code][Demo] | |
| Andrew Owens, Phillip Isola, Josh McDermott, Antonio Torralba, Edward H. Adelson, William T. Freeman Visually Indicated Sounds IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016 (oral). [Paper][Website][Video][Dataset (50GB)] | |
| Phillip Isola, Daniel Zoran, Dilip Krishnan, Edward H. Adelson Learning Visual Groups From Co-occurrences in Space and Time International Conference on Learning Representations, Workshop paper, 2016 [Paper] | |
2015 | |
| Daniel Zoran, Phillip Isola, Dilip Krishnan, William T. Freeman Learning Ordinal Relationships for Mid-Level Vision International Conference on Computer Vision (ICCV), 2015. [Paper][Website][Code] | |
| Phillip Isola*, Joseph J. Lim*, Edward H. Adelson Discovering States and Transformations in Image Collections IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015 (oral). [Paper][Website][Dataset] | |
| Zoya Bylinskii, Phillip Isola, Constance Bainbridge, Antonio Torralba, Aude Oliva Intrinsic and Extrinsic Effects on Image Memorability Vision Research, 2015. [Paper][Website][Code][Dataset] | |
| Zhengdong Zhang, Phillip Isola, Edward H. Adelson Sparkle Vision: Seeing the World through Random Specular Microfacets 4th IEEE International Workshop on Computational Cameras and Displays, 2015. [Paper] | |
2014 | |
| Phillip Isola, Daniel Zoran, Dilip Krishnan, Edward H. Adelson Crisp Boundary Detection Using Pointwise Mutual Information European Conference on Computer Vision (ECCV), 2014 (oral). [Paper][Website][Code] | |
2013 | |
| Phillip Isola, Jianxiong Xiao, Devi Parikh, Antonio Torralba, Aude Oliva What Makes a Photograph Memorable? Pattern Analysis and Machine Intelligence (PAMI), 2013. [Paper][Website][Dataset] | |
| Phillip Isola and Ce Liu Scene Collaging: Analysis and Synthesis of Natural Images with Semantic Layers. International Conference on Computer Vision (ICCV), 2013. [Paper][Website] | |
| Michelle Borkin, Azalea Vo, Zoya Bylinskii, Phillip Isola, Shashank Sunkavalli, Aude Oliva, Hanspeter Pfister What Makes a Visualization Memorable? IEEE Transactions on Visualization and Computer Graphics (Infovis), 2013. [Paper][Website] | |
| Wilma A. Bainbridge, Phillip Isola, Aude Oliva The Intrinsic Memorability of Face Images. Journal of Experimental Psychology: General, 2013. [Paper][Website][Dataset] | |
| Aude Oliva, Phillip Isola, Aditya Khosla, Wilma A. Bainbridge What makes a picture memorable? SPIE Newsroom Article, 2013. [Article] | |
2012 | |
| Aditya Khosla*, Jianxiong Xiao*, Phillip Isola, Antonio Torralba, Aude Oliva Image Memorability and Visual Inception. SIGGRAPH Asia Technical Briefs (Invited Paper), 2012. [Paper] | |
| Forrester Cole, Phillip Isola, William T. Freeman, Fredo Durand, Edward H. Adelson Shapecollage: Occlusion-aware, example-based shape interpretation. European Conference on Computer Vision (ECCV), 2012. [Paper][Website] | |
| Wilma A. Bainbridge*, Phillip Isola*, Idan Blank, Aude Oliva Establishing a database for studying human face photograph memorability. Proceedings of the Annual Conference of the Cognitive Sciences Society, 2012. [Paper][Website][Dataset] | |
2011 | |
| Phillip Isola, Devi Parikh, Antonio Torralba, Aude Oliva Understanding the intrinsic memorability of images. NeurIPS, 2011. [Paper]Website] | |
| Phillip Isola, Jianxiong Xiao, Antonio Torralba, Aude Oliva What makes an image memorable? IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011. [Paper][Website][Dataset] | |
2008 | |
| Nicholas B. Turk-Browne, Phillip Isola, Brian J. Scholl, Teresa A. Treat Multidimensional visual statistical learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 2008. [Paper] |
