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Achievement: Pair ExtraordinaireAchievement: YOLOAchievement: Pull Sharkx2Achievement: Quickdraw

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lawun330/README.md

Greetings 👋 from La Wun Nannda

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Background

Started coding out of curiosity and gradually expanded into software development and AI.

  • 2018: Started programming with Arduino
  • 2019–2020: Expanded into robotics, machine learning, Python, Linux, IT automation, and web fundamentals
  • 2022–2025: BSc. in Computer Science | GPA: 3.88/4.0 | University of the People
  • 2026: SWE internships, QIntern 2026, backend development

Current Direction

  • Focus: Machine Learning | Quantum Computing
  • Engineering: Full-stack development with ML/AI integration
  • Long-term: Build deep expertise across software engineering, AI/ML, and quantum computing, with a focus on technologies still at the frontier

Tools Used In Projects

Full Stack Development:

Skill Icons

Web Services:

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Machine Learning:

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Others:

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  1. QML-for-Conspicuity-Detection-in-Production QML-for-Conspicuity-Detection-in-Production Public

    Forked from womanium-quantum/QML-for-Conspicuity-Detection-in-Production

    Quantum computing competition project — Womanium + Fraunhofer ITWM (2024)

    Jupyter Notebook

  2. quantum-portfolio-optimization-remake quantum-portfolio-optimization-remake Public

    Quantum computing competition project (remake) — WISER + Vanguard (2025)

    Linear Programming 1

  3. quantum-sentinel quantum-sentinel Public

    Team C (previously Team B) deliverables for the QuantumSentinel project from QIntern 2026 of QWorld

    Jupyter Notebook 1

  4. information-retrieval information-retrieval Public

    Information retrieval using basic versions of a web crawler, indexer, and search engine, along with supporting modules

    Python

  5. burmese-char-online-hwr burmese-char-online-hwr Public

    Online handwritten recognition for Burmese characters using various ML models (RNN, BiLSTM)

    Python 2

  6. cross-domain-burmese-ngram-lm cross-domain-burmese-ngram-lm Public

    Burmese n-gram language modeling on general and domain-specific corpora using KenLM and SRILM

    Jupyter Notebook 2