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Achievements

Achievement: YOLOAchievement: QuickdrawAchievement: Pull Sharkx2Achievement: Pair Extraordinairex2

Achievements

Achievement: YOLOAchievement: QuickdrawAchievement: Pull Sharkx2Achievement: Pair Extraordinairex2

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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 (Feb 2023 - April 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! 😊

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  1. CineNet CineNet Public

    Database-driven social forum for movie fans, featuring PostgreSQL for data handling and interactive SQL queries for personalised content and recommendations.

    Shell

  2. C-Network-Bomberman C-Network-Bomberman Public

    C-Network-Bomberman is a multiplayer Bomberman game written in C. Place bombs strategically and face your opponents in dynamic arenas. Chat functions are also included. You can even whisper message…

    C 2

  3. RetroGameGems RetroGameGems Public

    A loyalty card system for a retro video game store takes customers ("Chrononauts") on a journey through gaming history, while managers ("Chiefs") orchestrate this return to the past.

    EJS

  4. 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

  5. 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

  6. Blur-Image Blur-Image Public

    A Python tool for blurring images pixel by pixel using mathematical algorithms and also providing an approximate solution for sharpening the blurred image.

    Python