Research

Dr. Rahman's research interest focuses on the development and application of innovative statistical models and computational algorithms to extract meaningful insights from large-scale datasets. 

Recent Publications________________________________________________________________

§  Zhao, P., Yue, Z., & Rahman, M. S. (2026). Comparative analysis of shallow and deep learning methods for diabetes prediction using the Pima Indians dataset. In Proceedings of the IEEE International Conference on Electro/Information Technology (EIT). Presented; publication pending.

§  Fenton, S. H., Halpin, R., Wang, L., Rahman, M. S., & Keosayian, D. (2026). Preparing an AI-enabled workforce: Results of a needs assessment. In Opening the Personal Gate Between Technology and Health Care. IOS Press. https://doi.org/10.3233/SHTI260666

§  Rahman, M. S., & Reza, H. (2025). Hybrid deep learning approaches for accurate electricity price forecasting: A day-ahead US energy market analysis with renewable energy. Machine Learning and Knowledge Extraction, 7(4), 120. https://doi.org/10.3390/make7040120

§  Hasan, M., Rahman, M. S., Islam, S., Ahmed, T., Rifat, N., Ahsan, M., Gomes, R., & Chowdhury, M. (2023). Vision Transformer-based classification for lung and colon cancer using histopathology images. In 2023 International Conference on Machine Learning and Applications (ICMLA) (pp. 1300–1304). Jacksonville, FL, USA. https://doi.org/10.1109/ICMLA58977.2023.00196

§  Rahman, M. S., Reza, H., & Kim, E. (2023). A hybrid deep neural network model to forecast day-ahead electricity prices in the USA energy market. In 2023 IEEE World AI IoT Congress (AIIoT) (pp. 525–534). Seattle, WA, USA. https://doi.org/10.1109/AIIoT58121.2023.10174342

§  Rahman, M. S., Rifat, N., Ahsan, M., Islam, S., Chowdhury, M., & Gomes, R. (2023). Deep learning application for detection of malaria. In 2023 IEEE International Conference on Electro Information Technology (eIT) (pp. 1–5). Romeoville, IL, USA. https://doi.org/10.1109/eIT57321.2023.10187342

§  Chowdhury, M. M., Rifat, N., Ahsan, M., Latif, S., Gomes, R., & Rahman, M. S. (2023). ChatGPT: A threat against the CIA triad of cyber security. In 2023 IEEE International Conference on Electro Information Technology (eIT) (pp. 1–6). Romeoville, IL, USA. https://doi.org/10.1109/eIT57321.2023.10187355

§  Chowdhury, M., Rifat, N., Latif, S., Ahsan, M., Rahman, M. S., & Gomes, R. (2023). ChatGPT: The curious case of attack vectors' supply chain management improvement. In 2023 IEEE International Conference on Electro Information Technology (eIT) (pp. 499–504). Romeoville, IL, USA. https://doi.org/10.1109/eIT57321.2023.10187385

§  Rahman, M. S., & Reza, H. (2022). A systematic review towards big data analytics in social media. in Big Data Mining and Analytics, vol. 5, no. 3, pp. 228-244, September 2022, doi: 10.26599/BDMA.2022.9020009

§  Rahman, M. S., & Reza, H. (2021). Big data analytics in social media: A triple T (types, techniques, and taxonomy) study. In: Latifi, S. (eds) ITNG 2021 18th International Conference on Information Technology-New Generations. Advances in Intelligent Systems and Computing, vol 1346. Springer, Cham. https://doi.org/10.1007/978-3-030-70416-2_62

§  Alam, M. M., & Rahman, M. S. (2021). Data analysis for book reading preferences: Bangladesh perspective. Information Technology Journal, 20(1), 8–14.

§  Rahman, M. S., & Reza, H. (2020). Systematic mapping study of non-functional requirements in big data system. In 2020 IEEE International Conference on Electro Information Technology (EIT), Chicago, IL, USA, 2020, pp. 025-031, doi: 10.1109/EIT48999.2020.9208288

§  Ahammad, I., Khan, M. A., Rahman, M. S., Khan, T., & Nath, N. (2020). Giga-scale integration system-on-a-chip design challenges and noteworthy solutions. International Journal of Recent Technology and Engineering, 8, 741–746. https://doi.org/10.35940/ijrte.F7225.038620

§  Khan, M. A. R., Rahman, M. M., & Rahman, M. S. (2016). Optimal set-up and surface finish characteristics in electrical discharge machining on Ti-5Al-2.5 Sn using graphite. Perspectives in Science, 8, 440–443. Doi: https://doi.org/10.1016/j.pisc.2016.04.099

§  Rahman, M. S., Noor, M. M. E., Islam, T., Tiwari, R., Kalia, K., & Kumar, T. (2016). SSTL input/output standard based energy efficient multiplier design using Urdhva Tiryagbhyam on 28nm FPGA. International Journal of Control and Automation, 9(4), 245–252.

§  Nagah, S., Pandey, B., Kalia, K., Kaur, R., & Rahman, M. S. (2015). I/O standards based on green communication using Fibonacci generator design on FPGA. International Journal of Control and Automation, 8(8), 113–118.

§  Mahbub-E-Noor, M., Siddiquee, S. M. T., & Rahman, M. S. (2014). Evaluation of OpenStack (Havana Release) and CloudStack (4.3 Release) open source cloud solutions. Information Technology Journal, 13(16), 2508.

§  Rahman, M. S., Hossain, M. B., Hossain, M. J., & Baowaly, M. K. (2009). Performance comparison and improvement of broadcasting protocols in mobile ad-hoc network.

Book Publications____________________________________________________________

§  Broadcasting Protocols in Mobile Ad-hoc Network: Performance comparison, improvement, and suggestion, Author: Md. Saifur Rahman, ISBN-13: 9783659159220, Publication Date: June 2012.