I am a PhD candidate at MIT CSAIL advised by Polina Golland and a student researcher at Google with Daniel Duckworth and Suhani Vora. My research focuses on computer vision, particularly representations of 3D scenes. I also work on medical image analysis, including robust and interpretable techniques for both generative and discriminative models. I use diffusion models to make things.
I interned in the Computational Photography Group at Adobe working with Jiawen Chen and Cecilia Zhang. I previously worked with Jim Duncan and Julius Chapiro in the Yale Radiology Research Lab, and interned at Iterative Scopes. I am supported by the Takeda Fellowship and Siebel Scholarship. I received a B.S. in Biomedical Engineering at Yale, where I did research with Stuart Campbell.
Selected Publications
Interpolating between Images with Diffusion Models Project | Paper | Code | |
Spatial-Intensity Transforms for Medical Image-to-Image Translation Project | Paper | Code | |
Approximate Discretization Invariance for Deep Learning on Neural Fields Project | Paper | Video | Code | |
Automatic Segmentation of the Placenta in BOLD MRI Time Series Paper | Code | |
Pre-Trained Language Models for Interactive Decision-Making Project | Paper | Code | |
Deep learning–assisted differentiation of pathologically proven atypical and typical hepatocellular carcinoma (HCC) versus non-HCC on contrast-enhanced MRI of the liver Paper | |
Spatial-Intensity Transform GANs for High Fidelity Medical Image-to-Image Translation Project | Paper | Video | Code | |
Automated feature quantification of Lipiodol as imaging biomarker to predict therapeutic efficacy of conventional transarterial chemoembolization of liver cancer Paper | Code | |
A probabilistic approach for interpretable deep learning in liver cancer diagnosis Project | Paper | Talk | Code | |
Deep learning for liver tumor diagnosis part II: interpretable deep learning to characterize tumor features Project | Paper | Code | |
Deep learning for liver tumor diagnosis part I: development of a convolutional neural network classifier for multi-phasic MRI Paper | Code | |
The Role of Artificial Intelligence in Interventional Oncology: A Primer Paper | |
Slowing of contractile kinetics by myosin-binding protein C can be explained by its cooperative binding to the thin filament Paper |