Lucy Chai
Scholar

Lucy Chai

Google Scholar ID: bunnQWQAAAAJ
Massachusetts Institute of Technology
Computer VisionMachine LearningNeuroscience
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Citations & Impact
All-time
Citations
1,881
 
H-index
12
 
i10-index
13
 
Publications
20
 
Co-authors
0
 
Contact
Emaillrchai@mit.eduCVOpen ↗GitHubOpen ↗
Publications
3 items
Selfi: Self Improving Reconstruction Engine via 3D Geometric Feature Alignment
2025
Cited
0
LVT: Large-Scale Scene Reconstruction via Local View Transformers
2025
Cited
0
SplatVoxel: History-Aware Novel View Streaming without Temporal Training
2025
Cited
0
Resume
Academic Achievements
  • 1. Publications:
  • - 2023: DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data (NeurIPS 2023 Spotlight)
  • - 2023: Persistent Nature: A Generative Model of Unbounded 3D Worlds (CVPR 2023)
  • - 2022: Any-resolution training for high-resolution image synthesis (ECCV 2022)
  • - 2022: Totems: Physical Objects for Verifying Visual Integrity (ECCV 2022)
  • - 2021: Ensembling with deep generative views (CVPR 2021)
  • - 2021: Using latent space regression to analyze and leverage compositionality in GANs (ICLR 2021)
  • - 2020: What makes fake images detectable? Understanding properties that generalize (ECCV 2020)
  • - 2020: On the 'steerability' of generative adversarial networks (ICLR 2020)
  • - 2019: Evolution of semantic networks in biomedical texts (Journal of Complex Networks, 2019)
  • - 2018: Uncertainty Estimation in Bayesian Neural Networks and Links to Interpretability (Department of Engineering, University of Cambridge, 2018)
  • - 2018: Name and Face Matching (MITRE Corporation; US. Patent App. 16/042,958)
  • - 2018: Development of a Next Generation Tomosynthesis System (SPIE Medical Imaging Conference, 2018)
  • - 2017: Evolution of brain network dynamics in neurodevelopment (Network Neuroscience, 2017)
  • - 2016: Functional network dynamics of the language system
  • 2. Awards and Fellowships:
  • - NSF Graduate Research Fellowship
  • - Adobe Research Fellowship
  • - Meta Research PhD Fellowship
  • - Churchill Scholarship
Research Experience
  • 1. Adobe Research: Worked with Richard Zhang, Jun-Yan Zhu, Michael Gharbi, and Eli Shechtman
  • 2. Google Research (NYC): Worked with Noah Snavely, Zhengqi Li, and Richard Tucker
  • 3. Facebook: Collaborated with Ser-Nam Lim
Education
  • 1. Massachusetts Institute of Technology (MIT): Graduate student in Electrical Engineering and Computer Science, advised by Phillip Isola
  • 2. Churchill College, University of Cambridge: MPhil in Machine Learning, focusing on uncertainty and interpretability in Bayesian neural networks
  • 3. University of Pennsylvania: Bachelor's degree in Computer Science and Bioengineering, worked with Dr. Danielle S. Bassett on computational neuroscience, focusing on modeling neural processes as dynamic networked systems
Background
  • A graduate student in EECS at MIT CSAIL, advised by Phillip Isola. Current interests are in computer vision and controllable image synthesis.