An Efficient Machine Learning-Based Decision-Level Fusion Model to Predict Cardiovascular Disease. - Hafsa Binte Kibria; Abdul Matin (ICO, 2020)

A Comparative Study with Different Machine Learning Algorithms for Diabetes Disease Prediction. - Hafsa Binte Kibria; Abdul Matin; Nusrat Jahan; Sanzida Islam (CCE, 2021)

Hand Gesture Recognition Based Human Computer Interaction to Control Multiple Applications. - Sanzida Islam; Abdul Matin; Hafsa Binte Kibria (ICO, 2021)

Comparative analysis of two artificial intelligence based decision level fusion models for heart disease prediction. - Hafsa Binte Kibria; Abdul Matin; Sanzida Islam (ISIC, 2021)

The severity prediction of the binary and multi-class cardiovascular disease - A machine learning-based fusion approach. - Hafsa Binte Kibria; Abdul Matin (Comput. Biol. Chem., 2022)

An Ensemble Approach for the Prediction of Diabetes Mellitus Using a Soft Voting Classifier with an Explainable AI. - Hafsa Binte Kibria; Md. Nahiduzzaman; Md. Omaer Faruq Goni; Mominul Ahsan; Julfikar Haider (Sensors, 2022)

Lightweight Parallel CNN To Classify COVID-19 Associated Pneumonia From Chest X-Ray. - Hafsa Binte Kibria; Md. Ali Hossain (CCE, 2023)

Enhanced Network Intrusion Detection Using a Hybrid CNN-LSTM Approach on the UNSW-NB15 Dataset. - Zareen Tasnim Pear; Hafsa Binte Kibria (CCE, 2024)

A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI. - Oishi Jyoti; Hafsa Binte Kibria; Zareen Tasnim Pear; Md. Nahiduzzaman; Md. Faysal Ahamed; Khandaker Reajul Islam; Jaya Kumar; Muhammad E. H. Chowdhury (IEEE Access, 2025)

Compost maturity prediction and gas emissions monitoring: A sensor-based and interpretable machine learning approach. - Amith Khandakar; Azad Ibn Ashraf; Mohamed Arselene Ayari; Amin Esmaeili; Mohannad Aljarrah; Philips Michael; Md. Nahiduzzaman; Hafsa Binte Kibria; Vasiliki Maria Gerokosta; Abdul Ahad Shehbaz; Maryam Abdulla R. A Al-Mansoori; Farah Khattab (Comput. Electr. Eng., 2025)

An automated waste classification system using deep learning techniques: Toward efficient waste recycling and environmental sustainability. - Md. Nahiduzzaman; Md. Faysal Ahamed; Mansura Naznine; Md. Jawadul Karim; Hafsa Binte Kibria; Mohamed Arselene Ayari; Amith Khandakar; Azad Ashraf; Mominul Ahsan; Julfikar Haider (Knowl. Based Syst., 2025)