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Interviewed for the ‘CDS Incredible Alumni’ series

NYU Center for Data Science Mar 2021

#1 Winning Team at the DBTex Challenge

The DBTex Challenge Feb 2021

Top 10% Reviewer

NeurIPS 2020 Oct 2020

Best Capstone Project Award

NYU Center for Data Science Dec 2018

Recent Publications

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Saliency maps that identify the most informative regions of an image for a classifier are valuable for model interpretability. A common …
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Breast cancer is the most common cancer in women, and hundreds of thousands of unnecessary biopsies are done around the world at a …
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During the COVID-19 pandemic, rapid and accurate triage of patients at the emergency department is critical to inform decision-making. …
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In breast cancer screening, radiologists make the diagnosis based on images that are taken from two angles. Inspired by this, we seek …
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Medical images differ from natural images in significantly higher resolutions and smaller regions of interest. Because of these …
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All Deep Learning Programming

Recent Posts

This post explains how to unfold the undersampled, aliased image to the indices in the reconstruction matrix in SENSE. In short I …
Last updated on 2 min read

In the previous post I explained that, after a certain point, improving efficiency of the data loaders or increasing the number of data …
Last updated on 5 min read

Have you wondered why some of your training scripts halt every n batches where n is the number of loader processes? This likely means …
Last updated on 4 min read

‘Processing Megapixel Images with Deep Attention-Sampling Models’ (referred as ‘ATS’ below) [1] proposes a new …
Last updated on 4 min read

The main claims of the paper [1] A certain level of localization labels are inevitable for WSOL. In fact, prior works that claim to be …
Last updated on 4 min read
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