Pranav Kulkarni

CS + Math @ UMD • Software Engineer @ UM2ii

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Pranav Kulkarni is a bioinformatics software engineer at the University of Maryland Medical Intelligent Imaging Center (UM2ii) center. He received his B.S. in Computer Science and B.S. in Mathematics from the University of Maryland, College Park. His research focuses on the overarching goal of bringing AI from bench to bedside, by pioneering advances in federated lifelong learning frameworks to facilitate collaboration between distributed research groups, optimization of AI-assisted clinical decision-making by reducing burden of data curation, data annotation, and training/inference, and the implication of adversarial attacks on fairness and bias in medical imaging AI and how they might propagate. In the near future, Pranav aspires to attend graduate school to carve his path as a future computer scientist.

News

Apr 2024 One paper accepted to MIDL 2024. One paper accepted to DCAMI Workshop at CVPR 2024.
Jan 2024 Four abstracts accepted to SIIM 2024.
Jan 2024 Three abstracts accepted to ASNR 2024.
Dec 2023 One paper accepted to Journal of Digital Imaging.
Nov 2023 Two abstracts accepted to RSNA 2023.
Nov 2023 One paper accepted to Journal of the American College of Radiology.
Oct 2023 Five abstracts accepted to SIIM CMIMI 2023.
Sep 2023 One paper accepted to Radiology.
Aug 2023 One abstract accepted to MLHC 2023.
Jan 2023 One abstract accepted to SIIM 2023.
Nov 2022 One abstract accepted to Medical Imaging meets NeurIPS Workshop at NeurIPS 2022.

Selected Publications

  1. MIDL 2024
    Hidden in Plain Sight: Undetectable Adversarial Bias Attacks on Vulnerable Patient Populations
    Pranav Kulkarni, Andrew Chan, Nithya Navarathna, Skylar Chan, Paul H. Yi, and Vishwa S. Parekh
    In Medical Imaging with Deep Learning Jul 2024
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  2. CVPR 2024
    Privacy-Preserving Collaboration for Multi-Organ Segmentation via Federated Learning from Sites with Partial Labels
    Adway Kanhere, Pranav Kulkarni, Paul H. Yi, and Vishwa S. Parekh
    In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops Jun 2024
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  3. Preprint
    Surgical Aggregation: Federated Class-Heterogeneous Learning
    Pranav Kulkarni, Adway Kanhere, Paul H. Yi, and Vishwa S. Parekh
    arXiv preprint arXiv:2301.06683 Jan 2024
    PDF
  4. Preprint
    ISLE: An Intelligent Streaming Framework for High-Throughput AI Inference in Medical Imaging
    Pranav Kulkarni, Sean Garin, Adway Kanhere, Eliot Siegel, Paul H. Yi, and Vishwa S. Parekh
    arXiv preprint arXiv:2305.15617 Dec 2023
    PDF
  5. JACR
    Economic and environmental costs of cloud for medical imaging and radiology artificial intelligence
    Florence X. Doo, Pranav Kulkarni, Eliot Siegel, Michael Toland, Paul H. Yi, Ruth C. Carlos, and Vishwa S. Parekh
    Journal of the American College of Radiology Dec 2023
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  6. Radiology
    Coarse Race and Ethnicity Labels Mask Granular Underdiagnosis Disparities in Deep Learning Models for Chest Radiograph Diagnosis
    Preetham Bachina, Sean P. Garin, Pranav Kulkarni, Adway Kanhere, Jeremias Sulam, Vishwa S. Parekh, and Paul H. Yi
    Radiology Nov 2023
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  7. NeurIPS 2022
    From Competition to Collaboration: Making Toy Datasets on Kaggle Clinically Useful for Chest X-Ray Diagnosis Using Federated Learning
    Pranav Kulkarni, Adway Kanhere, Paul H. Yi, and Vishwa S. Parekh
    Medical Imaging meets NeurIPS Workshop Nov 2022
    PDF