Rafiuzzaman Mohammad

About

Dr. Rafiuzzaman Mohammad is a distinguished academic and researcher currently serving as a faculty member at the British Columbia Institute of Technology (BCIT) and Northeastern University in Vancouver, British Columbia. Dr. Mohammad holds a Ph.D. in Electrical and Computer Engineering from the University of British Columbia (UBC), where his dissertation focused on developing an observation-based runtime configuration framework for next-generation software applications. His research interests encompass a wide range of fields, including data science, software development, applied machine learning, and the Internet of Things (IoT).

Dr. Mohammad instructs courses in data analytics, service-based architectures, and UX/UI development, while also contributing to curriculum development in the B.Sc. in Applied Computer Science program. He supervises industry-sponsored student projects, guiding teams in real-world software development initiatives. His noteworthy projects include a fixed-wing drone simulator for agricultural applications and an advanced hand hygiene monitoring system utilizing machine learning.

Dr. Mohammad has extensive experience in academia, having previously served as a graduate teaching assistant at UBC for several years, and as a lecturer at Manarat International University in Bangladesh. His industry experience includes roles as a project manager and lead Android developer, where he led teams to develop innovative digital advertising solutions.

Recognized for his academic excellence, Dr. Mohammad has received multiple awards, including the International Doctoral Fellowship and the Turkish Presidential Award. He is an active contributor to the academic community, with numerous publications in reputable journals and conferences, and is involved in outreach activities aimed at enhancing student engagement and community participation.

Selected Publications

• Rafiuzzaman M, Gopalakrishnan S, Pattabiraman K. Co-Approximator: Enabling Performance Prediction in Colocated Applications. ACM Transactions on Embedded Computing Systems. 2024.
• Rafiuzzaman M, An observation-based runtime configuration framework for the front-end network edge (Doctoral dissertation, University of British Columbia). 2023.
• Rafiuzzaman M, Gopalakrishnan S, Pattabiraman K. π-Configurator: Enabling Efficient Configuration of Pipelined Applications on the Edge. In2022 IEEE/ACM Seventh International Conference on Internet-of-Things Design and Implementation (IoTDI) 2022 May 4 (pp. 156-169). IEEE.
• Rafiuzzaman M, Gascon-Samson J, Pattabiraman K, Gopalakrishnan S. Failure prediction in the internet of things due to memory exhaustion. InProceedings of the 34th ACM/SIGAPP Symposium on Applied Computing 2019 Apr 8.
• Gascon-Samson J, Rafiuzzaman M, Pattabiraman K. Thingsjs: Towards a flexible and self-adaptable middleware for dynamic and heterogeneous IoT environments. InProceedings of the 4th Workshop on Middleware and Applications for the Internet of Things 2017 Dec 11
• Gascon-Samson J, Rafiuzzaman M, Pattabiraman K. SmartJS: dynamic and self-adaptable runtime middleware for next-generation IoT systems. InProceedings Companion of the 2017 ACM SIGPLAN International Conference on Systems, Programming, Languages, and Applications: Software for Humanity 2017 Oct 22 (pp. 51-52).