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leon-dream1/README.md

Hi πŸ‘‹, I'm Nahidul Islam

Typing SVG


πŸ‘©β€πŸ’» About Me

I am a Software Engineer and a Computer Science & Engineering graduate with a strong passion for scalable web architectures, System Design, and DevOps, with a vision to transition into advanced Machine Learning and Data Science roles in the future.

Currently, I am working professionally as a Backend Developer, where I focus on building robust APIs, optimizing database performance, and containerizing applications for stable deployments. Alongside my core industry role, I have a deep research interest in Deep Learning, Computer Vision, and Explainable AI (XAI), aiming to bridge the gap between high-performance backend systems and intelligent AI solutions.

I thrive on solving real-world complex problems, designing high-concurrency systems, and continuous learning.

  • πŸ’Ό Currently working as a Backend Developer πŸš€
  • 🌱 Expanding my skillset in Next.js, Advance TypeScript, Microservices, and Cloud Integration (AWS & Docker)
  • πŸ”­ Focused on improving backend architecture, high-concurrency optimization, and ML model integration
  • πŸ’‘ Interested in scalable systems, data-driven solutions, and automated CI/CD pipelines
  • 🀝 Open to collaborative tech projects, technical discussions, and open-source contributions
  • πŸ“« Reach me at: nahidulislam019045@gmail.com

πŸ› οΈ Tech Stack

βš™οΈ Backend Architecture & Databases

NodeJS
ExpressJS
TypeScript
PostgreSQL
MongoDB
Redis

☁️ DevOps & Cloud Integration

Docker
AWS
Git

πŸš€ Frontend Development

Next.js
React
TailwindCSS
JavaScript

πŸ€– Machine Learning / Data Science (Learning)

Python
PyTorch
Scikit-Learn
NumPy
Pandas
Matplotlib
Seaborn

Supervised Learning
Unsupervised Learning
Deep Learning
Computer Vision
Explainable AI (XAI)
NLP

πŸ› οΈ Tools & Other Skills

  • Git & GitHub for version control
  • REST API design & integration
  • Deployment on Netlify, Vercel & Firebase Hosting
  • Familiar with Agile workflow & teamwork

πŸ”¬ Research Interests & Projects

  • Skin Lesion Classification using Swin Transformer & XAI
    Developed a deep learning model utilizing Swin Transformers combined with Explainable AI (XAI) frameworks to classify skin lesions with high accuracy, ensuring model transparency for medical applications.
  • Fields of Interest: Computer Vision, Deep Learning Interpretability, Medical Image Processing.

πŸ“Š GitHub Stats

GitHub Activity Graph

🌐 Connect with Me

LinkedIn Portfolio Email


🎯 Coding Philosophy

"Writing clean, readable, and maintainable code is just as important as making it scale. Optimizing databases and containerizing environments is my way of solving the digital puzzles of tomorrow."


✨ β€œI believe learning never stops β€” every project is an opportunity to grow and share knowledge.” ✨

Pinned Loading

  1. elite-property elite-property Public

    Elite Property is a property management system that allows agents to add properties and users to purchase properties within their budget. The admin has the ability to manage all properties and user…

    JavaScript

  2. elite-property-server elite-property-server Public

    This is the server code for Elite Property, a property management system. For more information, please refer to the client repository.

    JavaScript

  3. hotello-booking-system-client hotello-booking-system-client Public

    Our Hotel Room Booking website offers a seamless experience with features such as email-password, Google, and Facebook login and registration. Visitors can browse featured rooms, and users can book…

    JavaScript

  4. hotello-booking-system-server hotello-booking-system-server Public

    This is the server code for Hotello Booking, a room booking sysytem. For more information, please refer to the client repository.

    JavaScript

  5. Contrastive-Learning-based-Skin-Lesion-classification-using-HAM10000 Contrastive-Learning-based-Skin-Lesion-classification-using-HAM10000 Public

    HAM10000 Skin Lesion Classification using Deep Learning with Supervised Contrastive Learning and Focal Loss. Two-phase pipeline for robust feature extraction and accurate classification.

    Jupyter Notebook

  6. choose-your-own-car-server choose-your-own-car-server Public

    TypeScript