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Learning, coding, and creating
:octocat:
Learning, coding, and creating
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AhmadJeddi/README.md

Hi there I'm Ahmad JeddiZahed

Typing SVG

LinkedIn ORCID Email GitHub

👋 About Me

I am a Computer Engineering graduate and AI Research Engineer focused on developing practical deep learning systems through research and experimentation.

My research interests include Speech Processing, Computer Vision, and efficient AI systems, with a focus on representation learning and reproducible experiments.

Currently, I am a member of an applied AI team, collaborating on real-world AI solutions in computer vision and speech processing.

🧠 How I Work

  • 🔎 Research-driven: studying ideas, papers, and architectures before implementation.
  • 💻 Engineering-focused: building modular, clean, and reproducible systems.
  • 🚀 Continuous learner: exploring new domains and turning ideas into working solutions.

🔬 Research Interests

Deep Learning • Speech Processing • Computer Vision • Representation Learning • Efficient AI Systems

⭐ Featured Projects

🔬 Research & AI Projects

🎙️ Speech Emotion Recognition Framework

A research framework comparing Log-Mel and WavLM representations using lightweight deep learning architectures.

Concepts: CNN • ECA Attention • GeM Pooling • Self-Supervised Learning • Representation Efficiency

Research manuscript submitted for peer review.

🌱 Plant Disease Classification

A deep learning framework for plant disease classification using ResNet50 with DCBAM attention refinement on the PlantVillage dataset.

The project investigates attention-based feature enhancement for image classification and demonstrates a reproducible PyTorch training and evaluation pipeline.

Technologies: PyTorch • ResNet50 • DCBAM • Computer Vision • Attention Mechanisms

🧠 ResNet-DCBAM

A modular PyTorch implementation of ResNet50 enhanced with Channel and Spatial Attention mechanisms inspired by CBAM.

Technologies: PyTorch • CNN • Attention Mechanisms

💻 Software & Frontend Projects

📚 JavaScript Notes

A structured collection of JavaScript concepts, examples, and best practices for learning and reference.

🌐 Educational Landing Page

A responsive frontend project built with HTML5, CSS3, and JavaScript.

🎨 Bootstrap Grid System

A lightweight responsive grid system inspired by Bootstrap, built using CSS and Sass.

🖼️ Art-NFT

A responsive NFT landing page designed in Figma and implemented using HTML5, CSS3, and Bootstrap 5.

🛠️ Technical Stack

🤖 AI & Deep Learning

Python PyTorch TorchAudio Transformers Librosa Scikit--learn OpenCV NumPy Pandas Matplotlib

💻 Software Development

JavaScript TypeScript HTML5 CSS3 Bootstrap Sass

⚙️ Tools & Workflow

Git GitHub VS Code Linux Jupyter

📄 Research & Documentation

LaTeX Overleaf

💡 Philosophy

I believe impactful AI systems are built by combining research understanding, engineering discipline, and continuous experimentation.

Pinned Loading

  1. Plant-Disease-Classification Plant-Disease-Classification Public

    A ResNet50-DCBAM deep learning framework for plant disease classification using the PlantVillage dataset with reproducible training and evaluation pipelines.

    Python 3

  2. Resnet-DCBAM Resnet-DCBAM Public

    A clean and modular PyTorch implementation of DCBAM (Dual-Channel & Spatial Attention) integrated into a custom ResNet50 backbone. Includes attention modules, pretrained weight loading, layer freez…

    Python 10 1

  3. javascript-notes javascript-notes Public

    A comprehensive collection of JavaScript notes, examples, and best practices

    JavaScript 9 2

  4. Bootstrap-GridSystem Bootstrap-GridSystem Public

    **FloatGrid** is a minimalist, SCSS-powered grid system inspired by Bootstrap. Built with floats — not Flexbox or CSS Grid — it offers responsive columns, offsets, containers, and essential utility…

    CSS 2 1

  5. educational-landing-page educational-landing-page Public

    Responsive educational landing page built with HTML, CSS, and JavaScript

    HTML 3 1

  6. SafeIP SafeIP Public

    A lightweight network security tool that verifies IP location, validates network safety, and prevents access to protected links when unexpected location changes are detected.

    JavaScript