About Me

I'm a second-year PhD student at MIT, advised by Phillip Isola. I also collaborate with Yonglong Tian as a Student Researcher at Google Research.

I am supported by the NSF Graduate Research Fellowship, and previously by the MIT HDTV Grand Alliance Fellowship. I am broadly interested in generative models and representation learning, particularly data-centric approches. At the moment I'm working on the following questions:

  1. Learning from synthetic data: How can we harness generative models as a data source for visual representation learning? How do we generate "good" synthetic data?
  2. Human-aligned vision: How can we better align visual representations with human perception and perceptual preferences?
  3. Data-efficient learning: How can we sample and learn from data (real or synthetic) more efficiently?

Previously I got my bachelors in Computer Science and in Mathematics at MIT, working at the MIT Center for Brains, Minds, and Machines with Pawan Sinha and Xavier Boix. In the past I've also been fortunate to intern at DeepMind (large language models), D. E. Shaw (reinforcement learning research), Apple (applied machine learning), and Two Sigma (software engineering). In my free time I enjoy hiking, running, and tennis.


* indicates equal contribution

DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data
Stephanie Fu*, Netanel Tamir*, Shobhita Sundaram*, Lucy Chai, Richard Zhang, Tali Dekel, Phillip Isola.
NeurIPS, 2023 (spotlight).
Paper / Code / Website
Recurrent connections facilitate symmetry perception in deep networks
Shobhita Sundaram*, Darius Sinha*, Matthew Groth, Tomotake Sasaki, Xavier Boix
Scientific Reports, 2022.
Workshop on Generalization Beyond the Training Distribution in Brains and Machines, ICLR 2021.
Paper / Code / Poster
GAN-based Data Augmentation for Chest X-ray Classification
Shobhita Sundaram*, Neha Hulkund*
Workshop on Applied Data Science for Healthcare, KDD 2021


Do Neural Networks for Segmentation Understand Insideness?
Kimberly Villalobos*, Vilim Stih*, Amineh Ahmadinejad*, Shobhita Sundaram, Jamell Dozier, Andrew Francl, Frederico Azevedo, Tomotake Sasaki, Xavier Boix
Neural Computation, 2021

Paper / Code

Invited Talks


Other Writing