Md. Rakibul Hasan
Lecturer
Md. Rakibul Hasan is a Lecturer in the Department of Computer Science and Engineering (CSE) at Bangladesh University (BU). He holds both an MSc and a BSc from East West University (EWU), with CGPAs of 3.47 and 3.59, respectively. His academic and professional interests include data science, artificial intelligence, natural language processing, and machine learning, with a particular focus on Bangla-English language processing and emotion detection.
Academic Experience
Md. Rakibul Hasan is serving as a Lecturer in the Department of Computer Science and Engineering at Bangladesh University. Prior to joining Bangladesh University, he gained approximately two years of experience as a Teaching Assistant at East West University, contributing to academic support and student learning activities.
Professional Practice
He also worked as a Trainee Data Scientist at JoinVenture AI for two months, gaining practical exposure to data science and artificial intelligence applications. His academic and professional experience reflects a strong foundation in computational methods, data-driven analysis, and emerging AI technologies.
Research Work
Projects:
1. Movie Recommendation System: Developed a personalized movie recommendation system using Collaborative Filtering, implementing the algorithm from scratch in python.
2. Product Recommendation Chatbot: Built a personalized product recommendation chatbot for Bangladesh as capstone project in python.
3. Kidney stone detection project: Applied YOLO V8 baseline model, YOLO V10, YOLO V11, YOLO V12 with DINO v3 and Graph Attention Network (GAT) model for detecting kidney stone from CT scan images.
4. Lung Cancer cell detection: Built several models to compare the performance for detecting lung cancer cell from histopathology images.
5. Online E-Ticket System: Built a user-friendly ticket booking website with HTML, CSS, and JavaScript on the frontend and Django on the backend, featuring seat selection and downloadable PDF tickets.
GitHub profile: https://github.com/rakib034
1. Rashid, M.R.A., Hasan, K.F., Hasan, R., Das, A., Sultana, M., Hasan, M., 2024. A comprehensive dataset for sentiment and emotion classification from Bangladesh e-commerce reviews. Data in Brief 53, 110052. https://doi.org/10.1016/j.dib.2024.110052
2. Islam, M.M., Ahmed, Md.J., Shafi, M.B., Das, A., Hasan, Md.R., Rafi, A.A., Rashid, M.R.A., Niloy, N.T., Ali, Md.S., Chowdhury, A., Rasel, A.A.S., 2025. BDMANGO: An image dataset for identifying the variety of mango based on the mango leaves. Data in Brief 58, 111241. https://doi.org/10.1016/j.dib.2024.111241
3. Accepted paper titled ‘Histopathology Images-Based Deep Learning Prediction of Prognosis and Therapeutic Response in Small Cell Lung Cancer’ in ICDMIS 2024
4. Islam, M.M., Das, A., Shams, K., Hasan, Md.R., Hasan, K.F., Rashid, M.R.A., Chowdhury, A., Ali, M.S., Islam, M., Shahjalal, M., Masum, S., 2025. TFP-BD: An image dataset for Traffic Flow and Pedestrian movement analysis on Bangladeshi urban roads. Data in Brief 59, 111398. https://doi.org/10.1016/j.dib.2025.111398
5. M. R. A. Rashid, A. Das, K. F. Hasan, M. R. Hasan, M. Sultana, M. Hasan, R. U. Islam, R. A. Tuhin, and M. S. H. Khan, “BERT-KAN: Enhancing bilingual sentiment analysis in Bangladeshi e-commerce through fine-tuned large language models,” Natural Language Processing Journal, vol. 13, p. 100190, 2025, doi: https://doi.org/10.1016/j.nlp.2025.100190
6. Accepted a paper titled ‘Towards Annotation-Efficient Kidney CT Scan Classification: Supervised and Semi-Supervised Swin Transformer Frameworks’
7. Accepted a paper titled ‘CodeMixEcom-Emotion: A Large-Scale Bangla-English Review Corpus and Transformer-Based Benchmark for Fine-Grained Emotion Detection’
8. Aritra Das, Mohammad Rifat Ahmmad Rashid, Md. Rakibul Hasan, Karib Shams, Raihan Ul Islam, BDFlower: Growth Stage Flower Image Dataset for Precision Agriculture and Floriculture, Data in Brief, 2026, 112745, ISSN 2352-3409, https://doi.org/10.1016/j.dib.2026.112745
9. S. Hossen, A. Das, M. R. Hasan and M. R. Huq, "Fast, Fault-Tolerant, and Affordable: A Modern Data Lakehouse ETL Pipeline for Emerging Economies," 2025 28th International Conference on Computer and Information Technology (ICCIT), Cox's Bazar, Bangladesh, 2025, pp. 3440-3445, doi: 10.1109/ICCIT68739.2025.11491349
Google Scholar Profile: https://scholar.google.com/citations?hl=en&user=LfxLoyYAAAAJ
