Md Mostasim Mahmud

Software Engineer | Web Developer | System Administrator

AI Khan Lab Ltd.

December 2, 2023 - Present

🧬 At AI Khan Lab Ltd, I developed and managed a Laboratory Management System tailored for histopathology and cancer testing. 🏥 The system handles patient registration, report generation, inventory tracking, and more, streamlining the lab's operations and improving efficiency.

School Management System

Developed a comprehensive School Management System that enables schools to efficiently manage their websites, administrative tasks, and academic processes. This system provides an integrated platform for handling student information, academic schedules, communication, and more.

Technologies Used:

Backend: Django (Python) for robust server-side processing and API management.
Frontend: React and Next.js for dynamic and responsive user interfaces.
Database: PostgreSQL for secure and reliable data storage.

Key Features:

Student Information Management: Seamlessly manage student records, including personal details, academic performance, and attendance.
Scheduling and Timetabling: Automate the creation of class schedules and examination timetables.
Communication Tools: Integrated messaging system for efficient communication between teachers, students, and parents.
Exam Management: Streamline the creation, scheduling, and grading of exams with automated tools.
Attendance Management: Track and manage student attendance with real-time updates and reporting.
Invoice Management: Generate and manage invoices for school fees, events, and other expenses.
Fees Collection: Simplify the process of collecting and tracking school fees with integrated payment systems.
Transportation Management: Manage school transportation, including bus routes, schedules, and student assignments.
Website Management: Customizable school websites with content management capabilities.
Reporting and Analytics: Generate detailed reports and analytics to monitor school performance and student progress.

Laboratory Management System

Customizing Dolibarr ERP for Medical Laboratories This project focuses on the customization of Dolibarr ERP, an open-source enterprise resource planning system, tailored for medical laboratory management. Dolibarr’s modular structure allows for seamless adaptation to meet the unique requirements of healthcare environments, particularly in managing lab workflows, patient records, and report generation. Key custom modules include:

Gross Module:

Automates the documentation of tissue sample examinations.
Allows lab technicians to record size, shape, and other characteristics with image integration.
Ensures data is accurately captured and linked to patient records.

Transcription Module:

Integrates voice recognition to transcribe verbal findings from lab technicians and doctors.
Minimizes errors and speeds up documentation.

Doctor Module:

Provides doctors with streamlined access to lab results, patient records, and diagnostic tools.
Enables efficient collaboration with lab personnel and allows requesting additional tests through the system.

Automated Report Generation Module:

Compiles data from other modules (e.g., gross examinations, transcription) into cohesive reports.
Uses predefined templates to reduce manual reporting efforts and ensure consistency.

Histopath Lab Module:

Manages the examination of tissue samples under a microscope.
Integrates with other modules to streamline the diagnostic process for diseases like cancer.
Allows image attachments for more comprehensive reporting.

Cytopath Lab Module:

Focuses on cell-level analysis for diagnosing diseases such as cancers and infections.
Integrates with patient records and allows high-resolution image storage for accurate cell analysis.

Ecommerce Platform

Developed a robust Ecommerce Platform with a personalized recommendation system to enhance user experience. This platform provides seamless product browsing, secure payments, and efficient order management.

Technologies Used:

Backend: Django REST API for scalable and secure server-side operations.
Frontend: Next.js for dynamic and responsive user interfaces.
Database: PostgreSQL for reliable and efficient data storage.
Recommendation System: Collaborative filtering and machine learning algorithms for personalized product recommendations.

Key Features:

Product Catalog: Browse and search products with filters and categories.
User Authentication: Secure login and registration with JWT (JSON Web Tokens).
Shopping Cart: Add, remove, and manage items in the cart.
Payment Integration: Secure payment gateway integration for seamless transactions.
Order Management: Track orders, view order history, and manage returns.
Recommendation System: Personalized product recommendations based on user behavior and preferences.
Admin Panel: Manage products, orders, and users with an intuitive admin interface.
Responsive Design: Fully responsive UI for seamless browsing on all devices.

Recommendation System:

Uses collaborative filtering to recommend products based on user behavior and purchase history.
Implements machine learning algorithms to improve recommendation accuracy over time.
Provides personalized product suggestions on the homepage, product pages, and checkout.

Digital Yearbook

Developed a Digital Yearbook platform for an Upwork client, enabling schools to create, manage, and share yearbooks digitally. This platform simplifies the process of collecting and organizing student memories, photos, and achievements.

Technologies Used:

Backend: Django REST API for robust and scalable server-side operations.
Frontend: Next.js for a dynamic and responsive user interface.
Database: PostgreSQL for secure and efficient data storage.
Admin Panel: Jasmin Admin Panel for easy management of yearbook content and users.

Key Features:

Yearbook Creation: Schools can create and customize digital yearbooks with ease.
Photo Uploads: Students and teachers can upload photos and memories to the yearbook.
User Roles: Different roles for admins, teachers, and students with appropriate permissions.
Search and Filters: Easily search and filter yearbook content by name, year, or event.
Responsive Design: Fully responsive UI for seamless access on all devices.
Export Options: Export yearbooks as PDFs or share them digitally via links.
Admin Panel: Jasmin Admin Panel for managing users, content, and yearbook settings.

Project Highlights:

Collaborated with an Upwork client to deliver a tailored solution for digital yearbooks.
Implemented a user-friendly interface for schools to manage yearbooks effortlessly.
Integrated Jasmin Admin Panel for efficient content and user management.
Enabled seamless photo uploads and sharing for students and teachers.

Linux & Docker Skills

Intermediate Linux user with expertise in Ubuntu and Debian-based systems. Proficient in Docker, including advanced configurations like changing the Docker root directory. Passionate about system optimization and containerization.

Linux Skills:

Proficient in Ubuntu and Debian-based Linux distributions.
Experience with system administration, package management, and shell scripting.
Familiar with Linux file systems, permissions, and networking.
Skilled in troubleshooting and optimizing Linux systems.

Docker Skills:

Proficient in Docker containerization and orchestration.
Experience with Docker Compose for multi-container applications.
Familiar with Docker networking, volumes, and image management.
Advanced knowledge of Docker daemon configurations.

Achievements:

Successfully changed the Docker root directory from /var/lib/docker to another location to optimize storage usage.
Published a detailed guide on GitHub: Changing Docker Root Directory.

Key Projects:

Optimized Docker configurations for better resource management.
Automated deployment workflows using Docker and shell scripts.
Migrated legacy applications to Docker containers for improved scalability.

Professor Scraper

An open-source web scraping tool to collect data about professors from various online sources. Built with Django, Django Rest Framework (DRF), and PostgreSQL, this project provides a robust backend for managing scraped data.

Project Goal:

The Professor Scraper project aims to provide an efficient web scraping tool that collects data about professors from various online sources. This data can be used for analysis, academic purposes, or to enhance educational resources.

Features:

Web Scraping: Uses Beautiful Soup and Requests libraries to scrape information from designated websites.
API Development: Provides a RESTful API using Django Rest Framework for easy access to scraped data.
Data Storage: Supports PostgreSQL (recommended) or SQLite for database management, allowing for easy data persistence and retrieval.
CORS Handling: Includes configuration for Cross-Origin Resource Sharing (CORS) to enable frontend applications to communicate with the backend.
Environment Management: Utilizes django-environ for managing environment variables, making it easy to configure settings based on different environments (development, production).
Code Quality Tools: Integrated linting and formatting tools (Flake8 and Black) to maintain code quality and consistency.