Manoja H A

Technical Development Lead at Edge Case Research
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Contact Information
Location
Munich, Bavaria, Germany, DE
Languages
  • English Full professional proficiency
  • German Limited working proficiency
  • Kannada Native or bilingual proficiency

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Experience

    • United States
    • Information Technology & Services
    • 1 - 100 Employee
    • Technical Development Lead
      • Jun 2023 - Present

    • ML Software Engineer II
      • Jan 2023 - Jun 2023

    • ML Software Engineer
      • Jun 2020 - Dec 2022

      Edge Case Research’s mission is to ensure that everyone stepping into a self-driving car gets a safe ride and that every autonomous vehicle traveling through our neighborhoods is built safely from the ground up.

    • Germany
    • IT Services and IT Consulting
    • 1 - 100 Employee
    • Machine Learning Engineer
      • May 2020 - Jun 2020

      - Led a team to successfully develop and deliver MLOps solution for deep learning models- Played a role in the technology transfer as TerraLoupe GmbH exited via an asset deal with Edge Case Research Inc

    • Master Thesis Student
      • Sep 2019 - Apr 2020

      Domain: Deep Learning - Information Retrieval - Active LearningTopic: Large-Scale Similar Aerial Image Retrieval SystemThe primary goal of this project was to enhance the performance of deep-learning models by implementing an active learning framework for reducing data requirements and eliminating noise from labels, resulting in more efficient models.- Expertise in designing and implementing feature selection and extraction algorithms for large-scale aerial image retrieval systems based on semantic segmentation models.- Developed a query selection algorithm that leverages model uncertainty to achieve image retrieval similar to the edge case scenario.- Designed and implemented a noisy label detection algorithm, incorporating active learning framework based on image similarity search.- The active learning framework resulted in a significant improvement in the performance of the segmentation models compared to the regular training workflow. Show less

    • Machine Learning Engineer - Intern
      • Mar 2019 - Aug 2019

      - Utilized state-of-the-art neural network architectures for aerial imagery road and lane semantic segmentation in autonomous driving applications.- Designed and developed automated algorithms for creating high-definition road maps on aerial imagery.

Education

  • Technische Universität Chemnitz
    Master of Science - MS, Embedded Systems
  • Nitte Meenakshi Institute of Technology
    Bachelor of Engineering - BE, Electronics and Communications Engineering

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