I am a PhD candidate at MIT CSAIL advised by Polina Golland. My research focuses on 3D vision, including neural fields and trajectory estimation. I also work on medical image analysis, particularly robust and interpretable techniques for both generative and discriminative models. I use diffusion models to make things.
I currently collaborate with Andrea Tagliasacchi, Daniel Duckworth, and Vincent Sitzmann. 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
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 |
Fun AI Creations (more)
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