1. Hasan Mahmudul, Ishrak Islam, and KM Azharul Hasan. "Sentiment Analysis Using Out of Core Learning." 2019 International Conference on Electrical, Computer and Communication Engineering (ECCE). IEEE, 2019 (PDF Link)

2. Hasan, Mahmudul, et al. "Attack and anomaly detection in IoT sensors in IoT sites using machine learning approaches." Internet of Things 7 (2019): 100059 (PDF Link).

3. Das Dola, Tabassum Nawshin, Hasan Mahmudul, M.M.A Hashem. "Deep Neural Network Based Continuous Blood Pressure Estimation with Data Mining Techniques." 2019 5th International Conference on Advances in Electrical Engineering (ICAEE 2019) (PDF Link).

4. Peer Reviewer of "Superimposed Rule-based Classification Algorithm in IoT using One-Class Conditional Anomaly Detection" Proceedings of Engineering and Technology Innovation

5. B.Sc. Thesis: Mahmudul Hasan, Ishrak Islam, M.M.A Hashem "A Study on Non-invasive Blood Glucose Measurement Techniques and Predictions"

6. Tasnim, Nowshin, Mahmudul Hasan, and Ishrak Islam. "Comparisonal study of Deep Learning approaches on Retinal OCT Image." arXiv preprint arXiv:1912.07783 (2019). (PDF Link)

7. Md. Ahsan Habib, Md. Milon Islam, Muhammad Nomani Kabir, Motasim Billah Mredul and Mahmudul Hasan," Staircase Detection System for Visually Impaired People: A Hybrid Approach," Revue d'Intelligence Artificielle, Lavoisier, vol. 33, no. 5, pp. 327-334, Oct. 2019. https://doi.org/10.18280/ria.330501. [Scopus (SJR: 0.12, H Index: 13, Q4), Ei Compendex, dblp] (PDF Link).

8. Hasan M, Aziz M, Zarif M, Hasan M, Hashem M, Guha S, Love R, Ahamed S ,"Noninvasive Hemoglobin Level Prediction in a Mobile Phone Environment: State of the Art Review and Recommendations", JMIR Mhealth Uhealth 2021;9(4):e16806, URL: https://mhealth.jmir.org/2021/4/e16806, DOI: 10.2196/16806 [Impact Factor: 4.301]

9. Mojumder P., Hasan M., Hossain M.F., Hasan K.M.A. (2020) A Study of fastText Word Embedding Effects in Document Classification in Bangla Language. In: Bhuiyan T., Rahman M., Ali M. (eds) Cyber Security and Computer Science. ICONCS 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 325. Springer, Cham. https://doi.org/10.1007/978-3-030-52856-0_35. (Link )

10. Islam, M.M., Haque, M.R., Iqbal, H. et al. Breast Cancer Prediction: A Comparative Study Using Machine Learning Techniques. SN COMPUT. SCI. 1, 290 (2020). https://doi.org/10.1007/s42979-020-00305-w. (Link )

11. Rahat-uz-Zaman, Md, Shadmaan Hye, and Mahmudul Hasan. "Audio Future Block Prediction with Conditional Generative Adversarial Network." 2019 3rd International Conference on Electrical, Computer & Telecommunication Engineering (ICECTE). IEEE, 2019. (Link )

12. M. K. Hasan, M. A. Alam, D. Das, E. Hossain and M. Hasan, "Diabetes Prediction Using Ensembling of Different Machine Learning Classifiers," in IEEE Access, vol. 8, pp. 76516-76531, 2020, doi: 10.1109/ACCESS.2020.2989857. (Link)

13. Gupta, R., Le, H., Van Arnam, J. et al. Characterizing Immune Responses in Whole Slide Images of Cancer With Digital Pathology and Pathomics. Curr Pathobiol Rep 8, 133–148 (2020). https://doi.org/10.1007/s40139-020-00217-7. (Link)