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Researching privacy-first approaches to ML
💡
Researching privacy-first approaches to ML

Highlights

  • Pro

Organizations

@FeTS-AI

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sarthakpati/README.md

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Current Role

Software Architect & AI Researcher at Indiana University's Division of Computational Pathology, and Technical Lead at the Medical Working Group of MLCommons working on designing solutions for privacy-focussed AI in Healthcare.

I believe open software fosters better science, and thus have been involved in multiple open-source projects and their associated research studies, including the Federated Tumor Segmentation (FeTS) platform and the Cancer Imaging Phenomics Toolkit (CaPTk). I am currently focusing my efforts on the following:

Interests

  • Applying concepts of AI (with a focus on privacy) to solve problems in healthcare.
  • Committed to doing reproducible and deployable research.
    • Firm believer of the saying a weak algorithm that is well written & integrated is better than a strong algorithm that isn't.
  • Advocating for F.A.I.R. in research.
  • Helping people choose the correct career path.

How to reach me

patis [at] iu.edu

Pinned Loading

  1. mlcommons/GaNDLF mlcommons/GaNDLF Public

    A generalizable application framework for segmentation, regression, and classification using PyTorch

    Python 166 80

  2. IUCompPath/Reference_Material IUCompPath/Reference_Material Public

    Reading and reference material to get jump started with some related work I do

    1 1

  3. FeTS-AI/Challenge FeTS-AI/Challenge Public

    The repo for the FeTS Challenge

    Python 49 29

  4. securefederatedai/openfl securefederatedai/openfl Public

    An Open Framework for Federated Learning.

    Jupyter Notebook 737 207

  5. CBICA/FigureGenerator CBICA/FigureGenerator Public

    This helps creating high quality figures for use in manuscripts and presentations.

    Python 11 2

  6. CBICA/CaPTk CBICA/CaPTk Public

    Cancer Imaging Phenomics Toolkit (CaPTk) is a software platform to perform image analysis and predictive modeling tasks. Documentation: https://cbica.github.io/CaPTk

    C++ 182 65