M. Mustafa Rafique Headshot

M. Mustafa Rafique

Associate Professor

Department of Computer Science
Golisano College of Computing and Information Sciences
mmrvcs@rit.edu
585-475-4528
Office Hours
Monday: 2:30-4:30 pm; Wednesday: 2:30-4:30 pm; And by appointment
Office Location
GOL-3635
Office Mailing Address
20 Lomb Memorial Drive, (GOL) 70-3635, Rochester, NY 14623

M. Mustafa Rafique

Associate Professor

Department of Computer Science
Golisano College of Computing and Information Sciences

Education

BS in Computer Science, NUCES (Pakistan); MS, Ph.D. in Computer Science, Virginia Tech

Bio

Dr. M. Mustafa Rafique is a faculty in the Department of Computer Science at the Rochester Institute of Technology (RIT). He has more than fifteen years of professional and research experience developing practical solutions for large-scale enterprise applications, and creating innovative solutions for massively parallel, distributed, and high-performance computing systems for a variety of application domains.  Dr. Rafique's research interests lie broadly in experimental computer systems, encompassing distributed platforms for cloud and high-performance computing, Internet of Things (IoT), and emerging data analytics frameworks for machine learning, smarter cities, and cognitive systems. Prior to joining RIT, Dr. Rafique was a staff member in the High Performance Systems Group at IBM Research in Dublin (Ireland). He has also worked at NEC Labs (Princeton) and Qatar Computing Research Institute (QCRI) on designing innovative solutions for adaptive and efficient resource management in massively parallel computing systems. Dr. Rafique earned his MS and Ph.D. degrees in Computer Science from Virginia Tech in 2010 and 2011, respectively. He is a Senior Member of the IEEE.  In his spare time, Dr. Rafique plays badminton, tennis, bridge and chess.

Personal Links
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Areas of Expertise
Distributed and parallel systems
High-performance computing
Resource management in heterogeneous systems

Select Scholarship

Published Conference Proceedings
Arif, Moiz, et al. "Application-Attuned Memory Management for Containerized HPC Workflows." Proceedings of the Proceedings of the 38th IEEE International Parallel & Distributed Processing Symposium (IPDPS). Ed. IEEE. San Francisco, California, USA: IEEE, 2024. Web.
Assogba, Kevin, Bogdan Nicolae, and M. Mustafa Rafique. "Optimizing the Training of Co-Located Deep Learning Models Using Cache-Aware Staggering." Proceedings of the In Proceedings of the 30th IEEE International Conference on High Performance Computing, Data, and Analytics (HiPC). Ed. IEEE. Goa, India: IEEE, 2023. Web.
Maurya, Avinash, et al. "Towards Efficient I/O Pipelines using Accumulated Compression." Proceedings of the In Proceedings of the 30th IEEE International Conference on High Performance Computing, Data, and Analytics (HiPC). Ed. IEEE. Goa, India: n.p., 2023. Web.
Journal Paper
Javaid, Anam, et al. "Clustering-cum-Handover Management Scheme for Improved Internet Access in High-Density Mobile Wireless Environments." Journal of Sustainable Computing: Informatics and Systems, Elsevier North-Holland, Inc. 30. ISSN: 1573–0484 (2021): 0. Web.
Ijaz, Samia, et al. "Energy-makespan Optimization of Workflow Scheduling in Fog-cloud Computing." Journal of Computing, Springer. (2021): ISSN 1436-5057. Web.

Currently Teaching

CSCI-652
Distributed Systems
3 Credits
An introduction to the study of distributed systems. The course covers distributed system architectures such as client-server and peer-to-peer, distributed system design issues such as communication, fault tolerance, coordination, and deadlock, distributed system middleware such as remote method invocation (RMI) and tuple space, and the theory of distributed algorithms such as logical clocks and leader election. Students will also learn about ethical and legal concerns in computing and research. Programming projects are required.
CSCI-750
Fundamentals of Cloud Computing
3 Credits
This course examines the fundamental building blocks and current practices of cloud computing. It explores distributed computing models and technologies, Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), Software-as-a-Service (SaaS), virtualization and containerization, software-defined environments (SDE), microservices-enabled architecture, cloud-class storage systems, big data processing frameworks, federated clouds, cloud-hosted applications, security and privacy, legal and ethical considerations, and other advanced and research topics in cloud computing. Case studies will investigate both established and state-of-the-art systems. Students will critique and present existing work and develop a deeper understanding and limitations of the state-of-the-art cloud systems. They will also propose and complete a research project individually or in teams, and write a conference/journal quality paper.

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