Lucy Chai (original) (raw)
About me
I am a graduate student in EECS at MIT CSAIL, advised by Phillip Isola. My current interests are in computer vision and controllable image synthesis.
I spent two summers at Adobe Research working with Richard Zhang, Jun-Yan Zhu, Michael Gharbi, and Eli Shechtman. I spent some time in Google Research in NYC with Noah Snavely, Zhengqi Li, and Richard Tucker. I have also collaborated with Ser-Nam Lim at Facebook. Thanks to NSF Graduate Research Fellowship, Adobe Research Fellowship, and Meta Research PhD Fellowship for supporting my research!
Previously I was at Churchill College, University of Cambridge. I did an MPhil in Machine Learning, where I studied uncertainty and interpretability in Bayesian neural networks. I am extremely grateful for support from the Churchill Scholarship.
I completed my undergraduate degree at the University of Pennsylvania in Computer Science and Bioengineering. I worked with Dr. Danielle S. Bassett in computational neuroscience, focusing on modelling neural processes as dynamic networked systems.
Papers
| 2023 | |
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DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic DataStephanie Fu*, Netanel Y. Tamir*, Shobhita Sundaram*, Lucy Chai, Richard Zhang, Tali Dekel, Phillip Isola.NeurIPS 2023 (Spotlight)[Paper][Website][Code] |
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Persistent Nature: A Generative Model of Unbounded 3D WorldsLucy Chai, Richard Tucker, Zhengqi Li, Phillip Isola, Noah Snavely.Conference on Computer Vision and Pattern Recognition, 2023[Paper][Website][Code] |
| 2022 | |
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Any-resolution training for high-resolution image synthesisLucy Chai, Michael Gharbi, Eli Shechtman, Phillip Isola, Richard Zhang.European Conference on Computer Vision, 2022[Paper][Website][Code] |
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Totems: Physical Objects for Verifying Visual IntegrityJingwei Ma, Lucy Chai, Minyoung Huh, Tongzhou Wang, Sernam Lim, Phillip Isola, Antonio Torralba.European Conference on Computer Vision, 2022[Paper][Website][Code] |
| 2021 | |
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Ensembling with deep generative viewsLucy Chai, Jun-Yan Zhu, Eli Shechtman, Phillip Isola, Richard Zhang.Conference on Computer Vision and Pattern Recognition, 2021[Paper][Website][Code] |
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Using latent space regression to analyze and leverage compositionality in GANsLucy Chai, Jonas Wulff, Phillip Isola.International Conference on Learning Representations, 2021[Paper][Website][Code] |
| 2020 | |
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What makes fake images detectable? Understanding properties that generalizeLucy Chai, David Bau, Ser-Nam Lim, Phillip Isola.European Conference on Computer Vision, 2020[Paper][Website][Code] |
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On the "steerability" of generative adversarial networksAli Jahanian*, Lucy Chai*, Phillip Isola.International Conference on Learning Representations, 2020 [Paper][Website][Code] |
| 2019 |
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| Evolution of semantic networks in biomedical textsLucy R. Chai, Dale Zhou, Danielle S. Bassett_Journal of Complex Networks_, 2019. |
| 2018 |
| Uncertainty Estimation in Bayesian Neural Networks and Links to InterpretabilityLucy R. Chai_Department of Engineering, University of Cambridge_, 2018. [Thesis] [Code] |
| Name and Face MatchingJohn C. Henderson, Abigail Gertner, Jeffrey Zarella, Lucy R. Chai, Keith MillerMITRE Corporation; US. Patent App. 16/042,958. |
| Development of a Next Generation Tomosynthesis System Jeffrey E. Eben, Trevor L. Vent, Chloe J. Choi, Sushmitha Yarrabothula, Lucy Chai, Margaret Nolan, Elizabeth Kobe, Raymond J. Acciavatti, Andrew D. A. Maidment SPIE Medical Imaging Conference, 2018. [Paper] |
| 2017 |
| Evolution of brain network dynamics in neurodevelopmentLucy R. Chai, Ankit N. Khambhati, Rastko Ciric, Tyler M. Moore, Ruben C. Gur, Raquel E. Gur, Theodore D. Satterthwaite, Danielle S. Bassett_Network Neuroscience_, 2017. [Paper] [Code] |
| 2016 |
| Functional network dynamics of the language systemLucy R. Chai, Marcelo G. Mattar, Idan A. Blank, Evelina Fedorenko, Danielle S. Bassett_Cerebral Cortex_, 2016. [Paper] |
Teaching
Advances in Computer Vision, MIT
Teaching Assistant with Phillip Isola, Bill Freeman
Spring 2021
Fluid Mechanics (BE350), UPenn
Teaching Assistant with Prof. Dan Huh
Spring 2017
Automata, Computability, Complexity (CIS262), UPenn
Teaching Assistant with Prof. Aaron Roth
Fall 2016