About

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.

A current CV as of 12/2025 is available here.

 

Selected Projects

For full publication list, see Google Scholar.

A Gaussian Parameterization for Direct Atomic Structure Identification in Electron Tomography
Reformulating atomic electron tomography to optimize Gaussian atoms instead of voxelgrids, improving reconstructions and directly identifying atomic structures.
International Conference on Computational Photography, 2025.
Paper Code Video

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