Shreya Kate

Data Scientist I at hoopla Digital
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Contact Information
us****@****om
(386) 825-5501
Location
Austin, Texas, United States, US
Languages
  • English Native or bilingual proficiency
  • Hindi Native or bilingual proficiency
  • Marathi Native or bilingual proficiency

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Credentials

  • Fundamentals of Deep Learning for Computer Vision
    NVIDIA Deep Learning Institute
    Oct, 2020
    - Nov, 2024
  • py4e101x: Programming for Everybody (Getting Started with Python)
    edX
    Aug, 2019
    - Nov, 2024

Experience

  • hoopla Digital
    • United States
    • Entertainment Providers
    • 1 - 100 Employee
    • Data Scientist I
      • Sep 2021 - Present

      • Optimising search engine by building vocabularies for digital library platform ‘hoopla’ using elasticsearch • Generating recommendations on hoopla • Maintaining and building NoSQL data products in MongoDB Built a scraper to scrape and parse e-book, audiobook data from html pages from Amazon and Audible • Optimising search engine by building vocabularies for digital library platform ‘hoopla’ using elasticsearch • Generating recommendations on hoopla • Maintaining and building NoSQL data products in MongoDB Built a scraper to scrape and parse e-book, audiobook data from html pages from Amazon and Audible

  • Children's Hospital Los Angeles (CHLA)
    • United States
    • Hospitals and Health Care
    • 700 & Above Employee
    • Research Assistant, CIBORG Lab (Computational Imaging of Brain Organization Research Group)
      • Aug 2020 - Jul 2021

      • Cortical segmentation of 3D neonatal MRI images using deep learning (U-Net) to automate and fasten the process • Implemented U-Net architecture and deveopled the pipeline using Python, TensorFlow and Keras • Created data pipeline for resizing and resampling 3D images for the training model • Cross-validated the data while training to avoid overfitting • Achieved an accuracy of 85% on test data using dice coefficient and dice loss as metrics • Cortical segmentation of 3D neonatal MRI images using deep learning (U-Net) to automate and fasten the process • Implemented U-Net architecture and deveopled the pipeline using Python, TensorFlow and Keras • Created data pipeline for resizing and resampling 3D images for the training model • Cross-validated the data while training to avoid overfitting • Achieved an accuracy of 85% on test data using dice coefficient and dice loss as metrics

  • KPIT
    • India
    • Software Development
    • 700 & Above Employee
    • Software Engineering Intern
      • Aug 2018 - Dec 2018

      Project : Connected Automotive – Smart IoT solution for collecting performance metrics • Transmitted values of temperature, pressure, and humidity from automotive parts to the cloud • Microcontroller (STM32F4 Discovery board and Arduino) as control unit • Used Node-RED to send data to cloud ThingsBoard as IoT-cloud platform Project : Connected Automotive – Smart IoT solution for collecting performance metrics • Transmitted values of temperature, pressure, and humidity from automotive parts to the cloud • Microcontroller (STM32F4 Discovery board and Arduino) as control unit • Used Node-RED to send data to cloud ThingsBoard as IoT-cloud platform

Education

  • University of Southern California
    Master's degree, Electrical Engineering - Machine Learning and Data Science
    2019 - 2021
  • Vishwakarma Institute Of Technology
    Bachelor of Technology - BTech, Electrical, Electronics and Communications Engineering
    2015 - 2019
  • Centre Point School - India
    12th grade, Physics, Chemistry, Mathematics, English, Physical Education
    2013 - 2015
  • Centre Point School - India
    10th Grade, 95.8%
    2003 - 2013

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