Arjun Desai
I am a PhD student at Stanford, where I work at the
intersection of signal processing, machine learning, and
data systems.
I am advised by
Akshay Chaudhari
and
Chris Ré
and am affiliated with the Stanford AI Lab, Center for
Artificial Intelligence in Medicine and Imaging (AIMI),
and Center for Research on Foundation Models (CRFM).
  
  
  
  
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Research
I am broadly interested in how we can use machine learning
robustly, efficiently and at scale in practice. My
research focuses on the intersection of inverse problems
in signal processing and machine learning. I also work on
how we can build scalable deployment and validation
systems for challenging applications in heathcare and the
sciences.
For a full list of publications, please see
Google Scholar.
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VORTEX: Physics-Driven Data Augmentations for
Consistency Training for Robust Accelerated MRI
Reconstruction
Arjun Desai, Beliz Gunel, Batu Ozturkler,
Harris Beg, Shreyas Vasanawala, Brian Hargreaves,
Christopher Ré, John Pauly, Akshay Chaudhari
MIDL, 2022  
(Oral Presentation, Best Paper)
arXiv
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code
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SKM-TEA: A Dataset for Accelerated MRI Reconstruction
with Dense Image Labels for Quantitative Clinical
Evaluation
Arjun Desai, Andrew Schmidt, Elka Rubin,
Christopher Sandino, Marianne Black, Valentina Mazzoli,
Kathryn Stevens, Robert Boutin, Christopher Ré, Garry Gold,
Brian Hargreaves, Akshay Chaudhari
NeurIPS Datasets & Benchmarks, 2021
arXiv
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code
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dataset
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colab
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Noise2Recon: Enabling Joint MRI Reconstruction and
Denoising with Semi-Supervised and Self-Supervised
Learning
Arjun Desai, Batu Ozturkler, Christopher
Sandino, Robert Boutin, Marc Willis, Shreyas Vasanawala,
Brian Hargreaves, Christopher Ré, John Pauly, Akshay
Chaudhari
Accepted (Magnetic Resonance in Medicine), 2023
arXiv
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code
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The International Workshop on Osteoarthritis Imaging
Knee MRI Segmentation Challenge: A Multi-Institute
Evaluation and Analysis Framework on a Standardized
Dataset
Arjun Desai, Francesco Caliva, Claudia
Iriondo, {16 authors}, Akshay Chaudhari.
Radiology: Artifical Intelligence, 2021
arXiv
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code
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Technical Considerations for Semantic Segmentation in
MRI using Convolutional Neural Networks
Arjun Desai, Garry Gold, Brian Hargreaves,
Akshay Chaudhari
Preprint, 2019
arXiv
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code
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