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BSc Software Engineering Β· Sylhet, Bangladesh

MD Naahe
Uddin Laskar

|

Software engineer building AI-powered applications and conducting research in Deep Learning, Cryptography, and Adversarial ML.

200+ Problems Solved
7+ Projects Built
3+ Years Coding
AI
Python
Flutter
TensorFlow
React
const naahe = {
  role: "AI Researcher",
  focus: ["DeepLearning",
           "Cryptography"],
  status: "building πŸš€"
};

Who I Am

MD Naahe Uddin Laskar
Open to Opportunities

I'm a Software Engineering student at Metropolitan University Sylhet with a focused research interest in Artificial Intelligence, Cryptography, and system security. My work lives at the boundary of Deep Learning and security β€” specifically adversarial machine learning, steganography, and satellite image classification.

On competitive platforms like CodeChef, Codeforces, and HackerRank I've solved 200+ problems. I build full-stack applications across mobile and web

SWE Innovators Forum Volunteers Coordinator ResearchGate Author arXiv Researcher

Tech Stack

C / C++
Java
Python
JavaScript
Flutter / Dart
React.js
Node.js
TensorFlow
Keras
MySQL
MongoDB
Supabase
Firebase
Figma
Git / GitHub
n8n

Selected Work

Projects spanning ML research, full-stack web, mobile applications, and UI/UX design.

02
πŸ€–

AI Career Path

Mobile Application

Cross-platform mobile app with user authentication, screen navigation, and polished Material Design UI. Integrates Claude API via Supabase Edge Functions, full Riverpod state management, GoRouter navigation, and a PostgreSQL backend with RLS policies.

FlutterDartSupabase Claude APIRiverpodGoRouter
03
πŸ—ΊοΈ

PropertyConnect

UI/UX Design β€” Figma

High-fidelity real estate platform prototype featuring smart search filters, property listing grids, secure auth onboarding flows, and a multi-frame interactive prototype map with full responsiveness and design system components.

FigmaPrototypingDesign Systems Responsive Design
04
🏠

HomeSphere

Real Estate Platform β€” Full-Stack MERN

Full-stack real estate platform with property listings, advanced search filters, and RESTful backend APIs. Built on the MERN stack with a component-driven React frontend and scalable Express.js API layer.

MongoDBExpress.jsReact.jsNode.js
05
βœ…

Taskflow Pro

Web Application β€” Full-Stack MERN

Task management and productivity platform featuring intuitive workflows, task organization, and real-time collaboration. Implements a kanban-style interface backed by a robust Node.js and MongoDB API.

React.jsNode.jsExpress.jsMongoDB
06
πŸŽ“

University Management System

Desktop Application β€” Java

Desktop-based system for student registration, course management, and academic data operations. Built with a modular OOP architecture using Java GUI and File Handling for persistent data management.

JavaJava SwingOOPFile Handling
07
πŸ“Š

Student Management System

Desktop Application β€” Python

Python Tkinter GUI for student data storage, retrieval, and academic record management. Menu-driven interface backed by MySQL. Supports CRUD operations, search, and report generation.

PythonTkinterMySQL

Education & Work

πŸ“š Education

2022 β€” 2026
BSc Software Engineering
Metropolitan University, Sylhet
  • Modules aligned with German ECTS requirements for TU9 application
  • Focus: AI, Data Structures, Computer Networks, Cryptography
  • Competitive programming β€” CodeChef, Codeforces, HackerRank
2020 β€” 2021
Higher Secondary Certificate (HSC)
Scholarshome, Shahi Eidgah, Sylhet
2018 β€” 2019
Secondary School Certificate (SSC)
Scholarshome, Shahi Eidgah, Sylhet

πŸ’Ό Responsibilities

Jan 2023 β€” Dec 2024
Volunteers Coordinator
SWE Innovators Forum
  • Recruited volunteers for technical events and community initiatives
  • Trained team members on responsibilities and procedures
  • Oversaw operations and inter-team coordination
Ongoing
Independent Researcher
ResearchGate Β· arXiv
  • Research in Deep Learning, Adversarial ML, and Steganography
  • Satellite image classification with TensorFlow and Keras
  • Military cryptography and information hiding techniques

Research Interests

Active areas targeting publication on ResearchGate and arXiv

01

Deep Learning / Computer Vision

Satellite Image Classification with Vision Transformers

Comparative analysis of CNN architectures versus Vision Transformers for land-use classification and threat detection in satellite imagery. Benchmarking VGG16, ResNet50, EfficientNet, InceptionV3, and ViT under varying data conditions and computational constraints. Target venue: arXiv cs.CV.

Get In Touch

Let's work
together.

Open to research collaborations, software engineering roles, and conversations about AI, security, and graduate opportunities in Germany. Reach out through any of the channels below.