Computer Science and Engineering is at the intellectual forefront of the digital revolution that will define the 21st century. That revolution is in its early stages but is visible all around us. New scientific, economic and social paradigms are arising from computing science and being felt across all sectors of the economy and society at large. For accepting this technological challenge of 21st century, the Department of Computer Science and Engineering is one of the most pioneering soloist of MBSTU and the country since its commencement in 2003. The department is keen on pushing the boundaries of traditional education system and it is the optimum combination of knowledge generation and application that makes the distinctive feature of the Department.
Tasnim Bill Zannah, Sadia Islam Tonni, Md. Alif Sheakh, Mst. Sazia Tahosin, Afjal Hossan Sarower, and Mahbuba Begum, “Comparative Performance Analysis of Ensemble Learning Methods for Fetal Health Classification,” Informatics in Medicine Unlocked, Elsevier, May, 2025. (Scopus Indexed) (Q2)
"KL-FedDis: A Federated Learning Approach with Distribution Information Sharing Using Kullback-Leibler Divergence for Non-IID Data", Md. Rahad, Ruhan Shabab, Mohd. Sultan Ahammad, Md. Mahfuz Reza, Amit Karmaker, Md. Abir Hossain – published on Neuroscience Informatics, Elsevier, November 28, 2024, ISSN: 2772-5286.
Mst. Sazia Tahosin, Md. Alif Sheakh, Taminul Islam, Rishalatun Jannat Lima, Mahbuba Begum, "Optimizing brain tumor classification through feature selection and hyperparameter tuning in machine learning models", Informatics in Medicine Unlocked, Elsevier, 2023. https://doi.org/10.1016/j.imu.2023.101414 (Scopus Indexed) (Q2)
2025-03-15