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aminshennan/README.md

Hi there, I'm Amin Ahmed Alawad 👋

Portfolio LinkedIn Email

👨‍💻 Data Scientist | ML Engineer | Computer Vision Specialist

Dynamic Data Scientist with expertise in deep learning, computer vision, and NLP. Passionate about developing AI solutions that solve real-world problems. Currently specializing in fine-tuning large language models and building computer vision systems.

🔭 Current Focus

  • Deep learning for computer vision and media forensics
  • Parameter-efficient fine-tuning of large language models
  • Building production-ready ML pipelines and web applications

🛠️ Tech Stack

Python PyTorch TensorFlow scikit-learn OpenCV FastAPI Flask SQL Power BI Hugging Face

🎓 Education

  • B.Sc. Computer Science (Hons.) - Data Science Specialisation, Multimedia University (2020-2024)

💼 Experience

  • Data Analyst Intern at SRKK (10/2023 – 01/2024)

    • Automated financial KPI dashboards in Power BI and Microsoft Fabric
    • Engineered Python dataflows and scheduled refreshes

  • Data Analyst Intern at Asian Football Confederation (AFC) (07/2023 – 10/2023)

    • Developed a comprehensive Power BI match analytics dashboard
    • Integrated 15+ interactive slicers and KPI cards

🚀 Featured Projects

Media Forgery Detection Scientific Paper Summarizer
Arabic Sign Language Sentiment Analysis

📫 Let's Connect!

⭐️ From aminshennan

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  1. Forgery_Detection_with_ViT_and_RestNet Forgery_Detection_with_ViT_and_RestNet Public

    Deep learning system achieving 95.36% accuracy in media forgery detection using hybrid ResNet50+ViT architecture. Optimized for 20% training data efficiency with PyTorch, OpenCV, and Flask-based in…

    Jupyter Notebook

  2. Hand-Sign-language-detection Hand-Sign-language-detection Public

    Arabic sign language recognition system using transfer learning (ResNet101V2) and YOLO-based hand detection. Benchmarks CNN, LSTM, and GNN architectures with multi-metric evaluation framework.

    Jupyter Notebook

  3. Scientific-Paper-Summarization-via-LoRA-Tuned-FLAN-T5-XXL- Scientific-Paper-Summarization-via-LoRA-Tuned-FLAN-T5-XXL- Public

    NLP pipeline with parameter-efficient LoRA fine-tuning on FLAN-T5-XXL (11B params). Achieves +2.6 ROUGE-1 improvement with <1% trainable parameters and 8-bit quantization for scientific paper summa…

    Jupyter Notebook

  4. Sentiment-Analysis-of-Women-s-Clothing-E-Commerce-Reviews-Using-Machine-Learning Sentiment-Analysis-of-Women-s-Clothing-E-Commerce-Reviews-Using-Machine-Learning Public

    Multi-architecture sentiment analysis (LSTM, CNN, FNN) with GloVe embeddings and Bayesian hyperparameter optimization. Comprehensive evaluation of e-commerce review classification with F1-score met…

    Jupyter Notebook