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About me



  • 2023 - 2023
    Johnson & Johnson, Titusville, New Jersey, USA

    R & D Data Sciences Intern

    • Utilized Detectron2 with preloaded Panoptic FPN weights, a robust deep learning model for object

    detection, to perform nuclei segmentation in pan-cancer images by training on panoptic segmented whole-
    slide images from the TCIA dataset.

    • Optimized nuclei segmentation pipeline by employing distributed data parallelism technique, leveraging
    the Ray Tune Python library to parallelize the predictions across multiple GPUs. This approach led to a
    linear improvement in computational time with the increasing number of GPUs.