I am a postdoc at UC Berkeley with Laura Waller. I work on applications of machine learning and computer vision to inverse problems in imaging.

Previously, I did my PhD at MIT with Polina Golland, 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