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ReTelect/README.md

Majd Najeh | Software Engineer & Technical Architect

Dedicated to mastering Low-Level Mechanics, Systems Engineering, and Automated Media Pipelines. My focus lies in bridging the gap between Algorithmic Efficiency and Scalable Application Design.

🛠 Technical Ecosystem

Core Engineering & Languages

  • Systems Programming: C (Manual Memory Management, Pointer Arithmetic, Data Structures).
  • Application Logic: Python 3.x (Advanced Scripting, Context Managers, Decorators), TypeScript.
  • Data Persistence: SQL (SQLite, PostgreSQL), Schema Design, Query Optimization.
  • Web Architecture: Node.js, React, Flask (RESTful API Design).

Media & AI Engineering

  • Digital Signal Processing: Automated Audio Thresholding, Frequency Analysis (SNR Calculation).
  • Video Orchestration: FFmpeg (Complex Filtergraphs, Codec Optimization, Hardware Acceleration).
  • AI Integration: Speech-to-Text (STT) Pipelines, Natural Language Processing (NLP) for signal segmentation.

DevOps & Environments

  • OS: Linux Power User (Pop!_OS), Shell Scripting (Bash/Zsh), Terminal-Centric Workflows.
  • Version Control: Git (Branching Strategies, Rebase Workflows).

📌 Architectural Case Studies

🎬 Silent Cutter (Audio-Driven Video Processor)

Technical Objective: Eliminate manual editing latency through algorithmic audio analysis and automated frame extraction.

  • Algorithmic Logic: Implemented a signal-to-noise ratio (SNR) analysis to detect and isolate "dead air" intervals within raw media streams.
  • Pipeline Engineering: Developed a multi-stage workflow leveraging Audio Extraction, VAD (Voice Activity Detection), and FFmpeg Concatenation.
  • Optimization: Utilized non-linear editing (NLE) logic to allow for manual fine-tuning, maintaining state between automated processing and user adjustments.

🗳️ Tideman (Ranked-Choice Voting System)

Technical Objective: Solve the Condorcet Paradox using graph theory.

  • Logic: Developed a Recursion-based Cycle Detection algorithm in C.
  • Complexity: Managed Adjacency Matrix representations to ensure the "strength of victory" is prioritized without creating locked loops in a directed graph.

🕵️ Imposter Detector

Technical Objective: Pattern recognition and anomaly detection within data streams.

  • Focus: Optimized Time Complexity for real-time analysis of large input sets to identify logical inconsistencies.

🎓 Certifications

  • HarvardX CS50x: Introduction to Computer Science (Memory, Algorithms, Web Security).

📫 System Interfacing

Pinned Loading

  1. tideman tideman Public

    C

  2. imposter-detector imposter-detector Public

    Python

  3. Aisilentcutter Aisilentcutter Public

    TypeScript

  4. HarborPluginManga HarborPluginManga Public

    Automated Multisrc Manga/Manhwa Plugin Generator for Harbor App.

    JavaScript 2