Rakib Hasan

Learner • Engineer • Researcher • Developer

personal overview

Rakib recently pursued a Bachelor of Science degree in Computer Science and Engineering at Daffodil International University. He is also an Associate Member of The Institution of Engineers, Bangladesh (IEB). He has a basic understanding of several programming languages, including C, Java, Python, Assembly, and Dart. Additionally, he is familiar with HTML, CSS, JavaScript, and PHP. He has foundational knowledge in data structures and algorithms, object-oriented programming, operating system, data mining, machine learning, and flutter. He has applied these skills in various projects. His strengths include being self-motivated, hardworking, disciplined, and a quick learner. His goal is to secure an honest and impactful position in his career, contributing to his nation.

research insights

Trend Prediction

This study utilized a 25-year dataset from the Dhaka Stock Exchange to predict stock trends with machine learning. Cross-validated results showed 85% accuracy, with LightGBM performing best. These findings were successfully deployed in web app, establishing a real-time framework for stock market analysis.

Cite As: R. Hasan, M. A. Badhon, M. H. Maruf, S. Ahmed, and S. H. Sanzit, “Machine Learning for Real-Time Stock Market Trend Prediction in Bangladesh: A 25-Year Comprehensive Analysis of Dhaka Stock Exchange with Web Application Deployment”, IJSRMT, vol. 5, no. 2, pp. 45–61, Feb. 2026.
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Eating Disorders

This study utilized a 57-item questionnaire to analyze neurobehavioral factors in eating disorders among students. Chi-square tests across six domains revealed significant associations. These findings were mapped to brain regions, establishing a neurobiological framework for understanding eating disorders.

Cite As: Hasan, R., Hosen, M. M., Sanzit, S. H., Talukder, M. A., & Mim, H. S. (2026). From Behaviour to Brain: A Statistical and Neurobehavioural Study of Eating Disorders. International Journal of Scientific Research and Modern Technology, 5(1), 28–44. https://doi.org/10.38124/ijsrmt.v5i1.1141
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Diabetes Forecast

This study used the Pima Indian Diabetes Dataset to build a predictive model for diabetes detection with machine learning. Six algorithms were analyzed, including Logistic Regression and Random Forest. Results showed Random Forest as the most accurate, offering timely and reliable detection of diabetes.

Cite As: Hasan R, Islam M, Hosen MM, Abdullah-Al-Kafi M, Radhakrishnan N. Predicting diabetes in women through machine learning. In2024 11th International Conference on Computing for Sustainable Global Development (INDIACom) 2024 Feb 28 (pp. 1307-1311). IEEE.
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Addiction Analysis

This study used body signals to develop a machine learning model for predicting types of smokers and drinkers. Algorithms, including Logistic Regression and Random Forest, were analyzed. Results showed Random Forest as the most accurate, making it the optimal choice for predicting smoking and drinking behavior.

Cite As: Hasan, Rakib, et al. "Classifying Different Types of Smokers and Drinkers by Analyzing Body Signals using Machine Learning." 2024 11th International Conference on Computing for Sustainable Global Development (INDIACom) 2024 Feb 28 (pp. 1060-1064). IEEE.
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project showcase

Deep Verify

Deep Verify is an AI image-authenticity system built to detect whether images are AI-generated or real. A custom ResNetRS50 network inspects uploads using preprocessing that remaps color distributions and normalizes features to improve detection and output a confidence percentage. Through a drag-and-drop web interface, Deep Verify returns "AI-Generated" or "Real" labels with transparent analysis feedback in-app.
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SafeNav AI

SafeNav AI is a smart navigation app built to improve road safety by providing real-time alerts about nearby accident-prone areas. Its machine-learning models trained on historical crash data predict high-risk zones and, combined with live GPS tracking, warn users when approaching dangerous locations. By showing map markers and continuous checks, SafeNav AI helps drivers and riders make safer travel choices.
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Quiz App

Quiz Application, developed with HTML, CSS, JavaScript, and PHP, enhances learning experience with functionalities. Administrators manage users by adding and removing teachers and students, while teachers create and manage diverse quiz topics. Students benefit from accessing default quiz topics and can participate in additional quizzes created by teachers, streamlining the educational environment.
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Safe-Guard

Safe-Guard is an advanced IoT-based safety monitoring system engineered to safeguard indoor environments from fire hazards and gas leaks in real-time. Integrated sensors continuously monitor air quality parameters like LPG, CO, and smoke levels, aiming to mitigate risks and ensure occupants' safety. With its sensor data analysis, Safe-Guard stands as a reliable solution for residential and commercial spaces.
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Portfolio App

Portfolio Application, built using Flutter, combines dynamic features and static content for a better and engaging user experience. It includes useful tools like a calculator, quiz, and weather app while also displaying information such as bio, skills, projects, and achievements. These unique features showcase the developer's abilities and highlight Flutter's versatility, making the app both practical and highly engaging.
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Voice Assistant

MOTU Voice Assistant, developed using Python, takes action by user commands, improving productivity by managing tasks like weather updates, time telling, providing top news, and information from online sources, playing videos from YouTube, telling jokes, random facts, and more. The purpose of the project is to build an application to reduce manual work and improve user productivity, and I named the assistant MOTU.
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R.M.S

The Restaurant Management System is constructed using assembly language to efficiently manage the details of the food menu and prices. Administrators, typically cashiers or managers, have exclusive access to this system. The primary objective behind this project is to develop an application program that automates the process of managing customer orders and generating bills, thereby minimizing manual intervention.
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calculator

The calculator developed using a shell script in Linux offers a range of functionalities. It supports arithmetic operations like addition, subtraction, multiplication, and division, along with exponentiation, square root calculation, and logarithmic functions. Additionally, it provides capabilities for converting numbers between binary, hexadecimal, and octal formats, meeting computational needs within Linux.
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L.M.S

Library Management System is built using C to manage the details of Admin, User, and Books. Librarian and his assistants are the admin and students and faculty members are the users of this system. The project is built at the administrator's end, so only the administrator has access. The purpose of the project is to build an application to reduce the manual work for managing the information of books, admin, and students.
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academic journey

B.Sc.

Attained a B.Sc. in Computer Science and Engineering with a CGPA of 3.84 out of 4.00. Developed skills in programming, data structures, machine learning, and software development through various projects.

H.S.C.

Acquired H.S.C. in Science with a GPA of 4.92 out of 5.00, building a strong foundation in mathematics, physics, and chemistry. Developed analytical skills and problem-solving abilities through academic excellence.

S.S.C.

Obtained S.S.C. in Science with a GPA of 5.00 out of 5.00, excelling in mathematics and science. Gained a strong academic foundation, fostering critical thinking and problem-solving skills for future studies.

J.S.C.

Achieved a GPA of 5.00 out of 5.00 in J.S.C., demonstrating strong academic performance. Built essential learning skills and a solid foundation in core subjects, paving the way for future academic success.

P.S.C.

Earned a GPA of 5.00 out of 5.00 in P.S.C., along with a General Grade Scholarship for outstanding performance. Developed a strong educational foundation and a passion for learning from an early stage.

skill badges

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+8801632093102

Email

rakib15-3948@diu.edu.bd

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