Nazrul University Scholars Secure ICT Research Fellowships

For the 2025–26 fiscal year, the Information and Communication Technology (ICT) Division has nominated a total of 48 students and researchers from universities at home and abroad to conduct research at the master’s, MPhil, doctoral, and post-doctoral levels in the information technology sector.

Following the recommendations of the selection committee formed to award scholarships and fellowships, and based on the final decision of the award committee, two students from Jatiya Kabi Kazi Nazrul Islam University have been selected among this year’s fellowship recipients.

Both recipients are postgraduate students of the 2023–24 academic session from the university’s Department of Computer Science and Engineering. The selected fellows are Fazle Rabbi Rizon and Sharmin Jahan.

Among them, Fazle Rabbi Rizon will conduct research on developing an effective method for skin cancer detection using machine learning. His study focuses on applying machine learning and artificial intelligence (AI)-based computer-aided diagnostic techniques to ensure the timely detection of skin cancer, particularly melanoma. The research involves model development and evaluation using the ISIC 2019 dataset to accurately classify different types of skin lesions. To enhance the model’s accuracy and robustness, techniques such as data augmentation, feature engineering, and ensemble learning have been employed.

Under the supervision of his department teacher Dr Tushar Kanti Saha, the researcher is now set to develop an effective and reliable AI-based diagnostic support system to assist physicians in the early detection and treatment of skin cancer.

Meanwhile, the other fellowship recipient, Sharmin Jahan, will work on harassment detection among female university students using machine learning. Her research aims to analyze the types and severity of harassment through information technology and to develop an effective detection system. In the initial phase of the study, data collected through questionnaires are used for data preprocessing, feature extraction, and machine learning-based model development to propose a structured framework for identifying harassment.

Through this research, the study highlights the potential of technology-driven solutions to ensure a safe and supportive environment for female students at the university level.

DBTech/CTN/MEM/OR