MD. Shohidul Islam

About Me

Professional Profile

I aim to build my career in research and development, data science, data analysis, and business analysis, with a strong focus on artificial intelligence, machine learning, and information technology. Through my research internship at the Advanced Machine Intelligence Research Lab (AMIR Lab), I gained hands-on experience in AI-driven projects and data analysis, which strengthened my technical and problem-solving skills. I am passionate about applying this expertise to real-world challenges, contributing to impactful projects, and growing as a professional who can lead teams and drive innovation.

Education

American International University - Bangladesh (AIUB)
Bachelor of Science in Computer Science and Engineering
Major: Information System | CGPA: 3.31
Passed in 2025

Relevant Courses:

Data Science Machine Learning AI Computer Vision Data Mining Python Computer Network Data Communication OS

Certifications

Cisco Certified
IT Essentials Course

Languages

Fluent in Bangla and English
Both verbal and written

Career Objective

Seeking a challenging position at a reputable organization where I can leverage my technical and managerial skills to contribute to the company's objectives while enhancing my expertise in current and emerging trends within the IT industry.

Technical Arsenal

Programming Languages

C C++ Java C# Python R

Deep Learning & AI

TensorFlow PyTorch Keras OpenCV Computer Vision CNN

Web Development

HTML JavaScript PHP CSS

Database Systems

MySQL MongoDB SQL Server

Tools & Platforms

Tableau GitHub MATLAB Visual Studio R Studio Assembly Language

Data Science & Analytics

Pandas Matplotlib Seaborn K-Means Clustering SciPy Statistical Analysis

Project Portfolio

Bee Collision Avoidance

Advanced computer vision project involving stereo camera recordings of bees to capture detailed movement data. Developed precise 2D and 3D trajectory reconstruction algorithms for behavioral analysis and collision avoidance studies.

Stereo camera calibration and setup
3D spatial measurements and tracking
Dataset annotation and trajectory analysis
Movement pattern insights and behavior modeling

Computer Vision OpenCV Python Camera Calibration MATLAB

Face Recognition Attendance System

Intelligent attendance management system using state-of-the-art VGGFace model for accurate face recognition. Implemented advanced preprocessing techniques and fine-tuning for optimal performance in real-world scenarios.

VGGFace model implementation and training
Real-time face detection and recognition
Automated attendance logging system
Advanced preprocessing and fine-tuning

Computer Vision OpenCV Python VGGFace Deep Learning

Titanic Data Cleaning & EDA

Comprehensive data science project involving extensive cleaning and exploratory data analysis of the Titanic dataset. Applied statistical methods and visualization techniques to uncover survival patterns and insights.

Data cleaning and preprocessing
Missing value imputation and feature engineering
Statistical hypothesis testing (t-tests)
Survival rate analysis by demographics

Python Pandas Matplotlib Seaborn Statistical Analysis SciPy

Cancer Dataset Analysis

Advanced data science project using R and R Studio for comprehensive cancer dataset analysis. Employed machine learning algorithms and statistical methods to identify factors influencing cancer outcomes.

Data preprocessing and feature scaling
K-Means clustering for pattern discovery
Missing value imputation techniques
Exploratory data analysis and visualization

Data Science K-Means Clustering R Studio Machine Learning R

Clothing Store Management System

Comprehensive Windows application for retail management with role-based access control. Features three distinct user roles (Owner, Manager, Shopkeeper) with specific permissions and functionalities for efficient store operations.

Multi-role user authentication system
Sales activity tracking and reporting
Inventory management and stock control
Modern UI with Guna UI components

C# Data Structures GunaUI SQL Server Visual Studio Algorithms

Aqua Ignis - Computer Graphics Game

Interactive two-player computer graphics game developed using C++ and OpenGL. Features Aqua (blue) and Ignis (red) characters with unique gameplay mechanics involving elemental interactions and cooperative puzzle-solving.

OpenGL-based graphics rendering
Elemental interaction system (fire vs water)
Cooperative gameplay mechanics
Dynamic hazards and obstacle navigation

C++ Computer Graphics OpenGL Game Development

Research Experience

Research Intern at Advanced Machine Intelligence Research Lab (AMIR Lab)

AMIR Lab focuses on reinforcement learning, algorithm development, and contributing to research publications in a collaborative academic environment.

Light-ROANet: Lightweight Retinal OCT Attention Network

97.06% Accuracy 369.8K Parameters Lightweight CNN

Developed lightweight CNN + attention model for OCT retinal disease classification
Outperformed ResNet and EfficientNet in both efficiency and performance
Used data augmentation, Grad-CAM, and TensorFlow/Keras for implementation
Enhanced interpretability through attention mechanisms

A Bee Flight Path Dataset for Bio-inspired Studies

Open Access 3D Trajectories 39.48 mm/sec

Developed open-access bee flight path dataset using stereo vision
Captured and reconstructed 3D trajectories of honeybees
Quantitative analysis including average speed and encounter distances
Applications in AI, swarm robotics, UAV navigation, and ecological monitoring

Get In Touch

Email
sojibaiub203@gmail.com

Phone
+880 1829 557610

Location
Kuratoli, Kuril, Dhaka-1212

LinkedIn Profile

YouTube Channel

GitHub Profile

ORCID Research ID

References

Professional Reference

Shah Riyad Chowdhury

Principal Software Engineer

Service Link LLC

+880 1611 666206

riyad36@gmail.com

Academic Reference

Dr. Debajyoti Karmaker

Associate Professor
Head Undergraduate Program

Department of Computer Science
Faculty of Science & Technology
American International University-Bangladesh

d.karmaker@aiub.edu

MD. SHOHIDUL ISLAM