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Achievement: Pair Extraordinairex3Achievement: Pull Sharkx3Achievement: YOLOAchievement: Quickdraw

Achievements

Achievement: Pair Extraordinairex3Achievement: Pull Sharkx3Achievement: YOLOAchievement: Quickdraw

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mathusanm6/README.md

👋 Hi there! I'm Mathusan

I'm a Software Engineer apprentice at Google and a MSc student in Data Science at Université Paris-Saclay, excited about using technology to solve meaningful problems and continuously learn along the way.

🌟 Projects

  • Amaze Voice Lab (Jan 2023 - May 2023)

    • Worked under the guidance of a researcher-professor over three months.
    • Implemented Whisper ML model for Automatic Speech Recognition (ASR), resulting in a 30% increase in operational efficiency and a 25% reduction in response latency, while enhancing system reliability.
    • Reduced processing time for voice recognition by 84% by integrating an optimised Whisper model instead of the base model.

  • Advanced Job Control Shell Emulator (Nov 2023 - Jan 2024)

    • Led a team to design and develop a Linux-optimised shell emulator using C, meeting a critical milestone in just 4 weeks.
    • Leveraged a 75% improvement in both manageability and scalability by restructuring and grouping related C files.
    • Improved development workflow by 25% by implementing GitHub Actions for Continuous Integration (CI), enhancing code integration and testing efficiency.
    • Accelerated deployment processes by 20% by leveraging Docker for Continuous Deployment (CD), ensuring rapid and reliable software delivery.

  • Blur-Image (Feb 2024 - Jun 2024)

    • Worked under the supervision of a researcher-professor in mathematics over three months as part of a research project.
    • Implemented Richardson-Lucy deconvolution algorithm to sharpen images previously blurred by a predetermined kernel.
    • Implemented Blind Richardson-Lucy deconvolution algorithm to sharpen image previously blurred by an organic blur or an unknown kernel.

  • Movie Recommendation System (Feb 2024)

    • Developed a movie recommendation system utilizing user-item matrix and the KNN classifier.
    • Gained insights into recommender systems's implementation using Python

🌐 Additional Skills

  • Multilingual: English (Fluent), French, Tamil (Native).
  • Interests: Competitive Programming, Machine Learning, Distributed Systems, Abstract Mathematics, Game development.

Feel free to reach out for collaborations or just to connect! 😊

Pinned Loading

  1. Unit-Tested-Leetcode-Solutions Unit-Tested-Leetcode-Solutions Public

    A collection of LeetCode problem solutions, rigorously tested with GoogleTest for C++ and pytest for Python.

    C++ 2

  2. Amaze-Voice-Lab Amaze-Voice-Lab Public

    The goal of this research project was to be able to control the movements of characters in a Maze game using real-time voice commands such as saying out loud Up, Down, Left or Right.

    Java

  3. Job-Control-Shell-Emulator Job-Control-Shell-Emulator Public

    A compact, C-developed shell emulator with advanced job control and system call integration, optimised for Linux environments.

    C

  4. Project-CGKS Project-CGKS Public

    Full-stack itemset mining app with Java (Spring Boot, Maven) backend, Python classifier API, React frontend, and Swagger UI documentation.

    Java 3

  5. Project-WORT Project-WORT Public

    This project aims to program using python, a small robot to participate in the World of Rasptank game.

    Python 1

  6. Critics-vs-Players-Analysis Critics-vs-Players-Analysis Public

    This data analysis examines the relationship between critic scores, sales (owners), player engagement, and pricing to determine the ROI of critic reviews.

    Jupyter Notebook