Education

B.Sc., Computer Science and Engineering, Ahsanullah University of Science and Technology, Bangladesh
M.S., Computer Science, University of Texas Rio Grande Valley

Background

Prior to joining the School of Information Science at the University of South Carolina, Mahmudul Robin was a master instructor of computer information technology at Indian River State College where he taught both online and face-to-face undergraduate courses. Before that, he worked as a research assistant at the University of Texas Rio Grande Valley. 

Awards

Robin received the Presidential Research Fellowship for outstanding research achievement from the University of Texas Rio Grande Valley. He was also awarded the G.R. and L.R. Ranganath Scholarship in recognition of his excellent academic performance during his Master’s studies.

Research

Robin’s research focuses on human behavior analysis, anomaly detection, data mining, chronic disease diagnosis, bioinformatics, and health informatics using advanced machine learning techniques. Most of his research is related to predictive analysis using machine learning, and he has expanded his work into health informatics. Much of his research involves data science and machine learning to analyze and experiment with health data. The results of his projects have been published in journals and conferences.

Teaching

Robin teaches in a variety of areas, including text mining in big data analytics, information design, programming, data analytics, and artificial intelligence, to undergraduate students in the iSchool. He believes in teaching through real-world examples and new technologies to make learning meaningful and engaging. His aim is to inspire lifelong learning by creating interactive environments that support every student’s unique abilities.

Publications

Jiang, H., Gao, Y., Sarwar, S. M., GarzaPerez, L., & Robin, M. (2021, December). Differential privacy in privacy-preserving big data and learning: Challenge and opportunity. In Silicon Valley Cybersecurity Conference (pp. 33-44). Cham: Springer International Publishing.

Rahman, M. M. U., Robin, M. H., & Taief, A. M. (2021). A new framework for video-based frequent iris movement analysis towards anomaly observer detection. International Journal of Image, Graphics and Signal Processing, 13(1), 13.

Robin, M. H., Taief, A. M., & Rahman, M. M. U. (2020, August). A novel approach to detect & track iris for a different and adverse dataset. In Proceedings of the 2020 4th International Conference on Big Data and Internet of Things (pp. 24-28).

Robin, M. H., Rahman, M. M. U., Taief, A. M., & Eity, Q. N. (2020, June). Improvement of face and eye detection performance by using multi-task cascaded convolutional networks. In 2020 IEEE Region 10 Symposium (TENSYMP) (pp. 977-980). IEEE.

Service

• iSchool BSIS Committee Member
• Reviewer of academic papers for conferences and journals