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RayanAlDwlah/README.md

AI engineer in Khobar, Saudi Arabia. I build LLM features that answer from a quoted source or leave the answer empty, and I check models for leakage before I trust a score.

Currently an AI Engineer (internship) at SAHAB in Riyadh. B.Sc. Computer Science, AI track, King Khalid University, 2026.

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  1. Genetic-Mutation-Detection-project Genetic-Mutation-Detection-project Public

    Pathogenic missense-variant classifier (XGBoost + ESM-2) on 195,098 variants. A leakage audit took PR-AUC from a leaky 0.955 to an honest 0.827 (calibrated).

    Jupyter Notebook

  2. Real-Time-Arabic-Sign-Language-Recognition Real-Time-Arabic-Sign-Language-Recognition Public

    Real-time Arabic sign-language letter recognition from a webcam: InceptionV3 transfer learning with MediaPipe hand cropping, plus an offline CNN + hand-geometry + XGBoost hybrid.

    Jupyter Notebook

  3. bank-account-fraud-detection bank-account-fraud-detection Public

    Fraud detection on the BAF (NeurIPS 2022) benchmark: the 98.4%-accurate model caught 17% of fraud, so models are judged by recall at 5% FPR (best 0.51).

    Jupyter Notebook

  4. land-use-permit-system land-use-permit-system Public

    Full-stack land-use permit workflow: Spring Boot 3 REST API with JWT roles, React SPA, PostgreSQL, Docker Compose. Built during my InnovationTeam internship.

    JavaScript