Amrit Virdee is a Machine Learning Engineer based in San Diego with nine years of experience applying ML to health informatics within pharmacy and clinical contexts. At CVS Health he contributes to improving personalized, accessible care by translating clinical needs into deployable ML solutions. A pharmacist by training turned practitioner-engineer, he blends domain knowledge with technical skill to build models that are clinically meaningful and operationally robust. He is an active open-source contributor to the fastai project, enhancing medical imaging support for multi-frame DICOMs and improving pixel-scaling utilities and tutorials used by the community. Colleagues describe him as pragmatic and detail-oriented, often surfacing edge-case data issues early in development. His work sits at the intersection of healthcare, ML tooling, and reproducible education for medical imaging.
Contributions:19 reviews, 8 commits, 16 PRs in 8 months
Contributions summary:Amrit primarily focused on updating and expanding the functionality of the `fastai` deep learning library, specifically in the context of medical imaging. Their contributions include modifications to the `show` function to handle multi-frame DICOM images, and the implementation of the `scaled_px` function to correctly scale pixel data. The user also contributed to tutorial notebooks on medical imaging, incorporating DICOM data loading and handling. These updates are targeted at improving and expanding functionalities related to medical imaging datasets.
Contributions:95 commits, 94 pushes, 1 branch in 1 year 10 months
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