MAJD AYOUB.SYS

[MODULE: WORKS] // SYS_DIR: /PROJECTS_OPENSOURCE/ACTIVE

Selected projects and contributions showing how I build AI, backend, security, and open source systems.

terminal CORE_SYS // PROJECT_01
CLASSIFICATION: GRADUATION_PROJECT // DEFENDED: JAN_2026

TruthLens: An AI-Assisted Credibility Assessment Platform

person_search Academic Supervisor: Eng. Nawal Al-Zabin
school Institution: Al-Balqa Applied University (BAU)

Strategic Vision: Complementary Intelligence. Built as a Decision Support System (DSS) that augments human judgment rather than replacing it. It delivers multi-dimensional, bilingual (Arabic & English) analysis synthesizing linguistic patterns, contextual cues, and source credibility against high-velocity misinformation.

TruthLens Interface Preview
Interface_Preview_01.png Res: 1080p
memory

Multi-Model Consensus

  • 01
    Qwen 3 (8B): Primary Reasoning Engine for complex semantic context and logical coherence analysis.
  • 02
    Phi-3 Mini (3.8B): Self-Healing Agent ensuring structural data integrity and JSON validation/repair.
  • 03
    Custom Logistic Regression: High-performance clickbait detection model deployed via Hugging Face.
layers

Advanced NLP Layer

Deep integration of CAMeL-BERT for Arabic linguistic nuances and Twitter-RoBERTa for English social sentiment. Augmented with Detoxify for hate speech moderation, SpaCy NER with Wikipedia API for factual entity enrichment, Tesseract OCR for visual text extraction, and FastText for vector embeddings.

dns

Performance Arch

Engineered on a Python 3 / FastAPI / Uvicorn stack for high-concurrency handling. Utilizes Celery/Redis for non-blocking background analysis. Implements Cold Start Elimination via persistent VRAM loading of models using Docker and CUDA acceleration.

database

Data Intelligence

Advanced Adaptive Scraping pipelines leveraging Newspaper3k and ScraperAPI. Integrated RAG (Retrieval-Augmented Generation) via ChromaDB for context injection. Deployment managed through Docker Compose microservices with Firebase real-time synchronization.

shield_lock

Defense & Privacy

Implements Proactive Threat Defense through VirusTotal API integration for automated URL scanning. Features Automated PII redaction for emails and phone numbers before analysis to ensure strict user privacy.

rocket_launch

Future Roadmap

System architecture confirms full Structural Readiness for Google News Fact Check API integration. Future iterations focus on scaling generative reasoning capabilities and expanding cross-platform social media monitoring modules.

Architecture Status Multi-Model Consensus + RAG Pipeline
HUD_GAUGE_01 // SYSTEM_VALIDATED
Zenodo Report description LinkedIn Article article
// Merged Open Source Contribution

OpenSSF cve-bin-tool

terminal
What it is: Merged Python pull request to OpenSSF cve-bin-tool, an open-source security scanner.
Problem: "cve_bin_tool.log.LOGGER is not a valid type" mypy logger typing issue (Issue #2870).
Fix: Explicit logging.Logger typing and restored centralized shared logger usage across files.
Result: Successfully resolved type checking errors and aligned related test coverage, resulting in a merged PR.
Stack: Python · mypy · logging · unit tests · security scanning
Proof / Links:
Merged PR #5724 open_in_new

PhishGuard Pro

security
What it is: AI/NLP-powered detector for phishing emails, SMS scams, and financial fraud.
What I built: BERT-based classification engine and security guidance utility.
Stack: BERT, RAG, Python, PyTorch
Proof / Links:
GitHub open_in_new

BayForge AI

architecture
What it is: Educational AI prototype for exploring California ADU zoning data.
What I built: Frontend interface and API routes for property analysis. ⚠️ Not legal advice; development stopped due to data integrity and legal-risk concerns.
Stack: Next.js, TypeScript, Tailwind CSS
Proof / Links:
GitHub open_in_new

MCP Notebook

library_books
What it is: Reference guide and development suite for Anthropic's Model Context Protocol (MCP).
What I built: Transport pattern simulators, interactive Vercel prototype, and notion engineering docs.
Stack: MCP API, Next.js, Vercel, Notion
Proof / Links:
GitHub open_in_new Open Demo open_in_new Notion open_in_new

Clickbait Detector

warning
What it is: Automated classification engine to identify and flag sensationalized headlines.
What I built: Machine learning classifier achieving 96.39% test accuracy.
Stack: NLP, Python, Scikit-learn
Proof / Links:
Hugging Face Model open_in_new

Fake News Detector

policy
What it is: Machine learning model trained to evaluate veracity and potential bias in news articles.
What I built: TF-IDF feature pipeline and logistic regression classifier packaged using Skops.
Stack: Scikit-learn, TF-IDF, Skops, Gradio, Hugging Face Spaces
Proof / Links:
Open Demo open_in_new

Full Stack Intern

terminal
What it is: Structured 280-hour Full-Stack Web Development Internship at Jordan Computer Society.
What I built: Flask/Jinja2 server-side prototypes, responsive layouts, SQL CRUD interfaces, and custom DOM logic.
Stack: Flask, Jinja2, SQL, Bootstrap, JavaScript
Proof / Links:
JCS Internship Certificate Verified