About

I’m a PhD student at the Harvard-MIT Division of Health Sciences and Technology, advised by Polina Golland. Previously, I did my undergrad in Electrical Engineering and Computer Science at MIT.

I am interested in machine learning, computer vision, and inverse problems. My PhD focuses on medical image reconstruction.

My work is supported by the NIH Neuroimaging Training Program, an NSF Graduate Research Fellowship, and a Google PhD Fellowship.

 

Selected Projects

For full publication list, see Google Scholar.

Data Consistent Deep Rigid MRI Motion Correction
Using test-time model-based optimization on neural network outputs to produce fast, high quality, physics-consistent motion-corrected MRI reconstructions.
Medical Imaging with Deep Learning, 2023 (Oral; Best Oral Award).
Paper Code Video MIT News

Joint Frequency and Image Space Learning for MRI Reconstruction and Analysis
A general purpose neural network layer that combines frequency and image space features for correcting artifacts in Fourier imaging.
Machine Learning for Biomedical Imaging, 2022.
Paper Code Video