Dr. Rizwan Mian

 Postdoctoral Fellow (2013 - 2014 )


York University
School of Information Technology
4700 Keele Street
Toronto, ON M3J 1P3

Dr. Marin Litoiu


Rizwan Mian holds a B.Sc. (Hons) and an Mphil from the University of Manchester, UK. He completed his Ph.D. at Queen’s University Canada, and is currently a post doctorate fellow at York University Canada. Research interests include processing large unstructured data, data mining, and cost and performance models.

Research Interests

  • Cloud computing

  • Big Data management and processing

  • Data mining

  • machine learning

  • predictive analytics

  • performance and cost models


  • Doctor of Philosophy (PhD) in Computer Science, Queen’s University, Canada
    Database Systems Lab, 2009-2013
    Advisors: Prof. Patrick Martin, Prof. Farhana Zulkernine
    Thesis: Cost-Effective Resource Configurations for Executing Data-intensive Workloads in Public Clouds.

  • Masters of Philosophy (MPhil) in Computer Science bypassing MSc., The University of Manchester, UK
    Software Systems
    Advisor: Prof. John Gurd
    Thesis: Managing distributed information for performance control of Grid-based applications.

Selected Publications

[1]    R. Mian, P. Martin, F. Zulkernine and J.L. Vazquez-Poletti, “Cost-Effective Resource Configurations for Multi-tenant Database Systems in Public Clouds,” IEEE Transactions on Parallel and Distributed Systems (TPDS), 2014, pp. submitted.
[2]    R. Mian, et al., “Near-Clouds: Bringing Public Clouds to Users’ Doorsteps,” Proceedings of the nineteenth IEEE Symposium on Computers and Communication (ISCC), 2014, pp. (submitted), Madeira, Portugal.
[3]    R. Mian, "Cost-Effective Resource Configurations for Executing Data-Intensive Workloads in Public Clouds (PhD Thesis)," School of Computing, Queen's University, 2013 [Online] Retrieved on. http://qspace.library.queensu.ca/jspui/bitstream/1974/8497/1/Mian_Rizwan_201311_PhD.pdf.
[4]    R. Mian, P. Martin, F. Zulkernine and J.L. Vazquez-Poletti, “Towards Building Performance Models for Data-intensive Workloads in Public Clouds,” 4th ACM/SPEC International Conference on Performance Engineering (ICPE), ACM, 2013, pp. 259-270, Prague, Czech Republic.
[5]    R. Mian, P. Martin and J.L. Vazquez-Poletti, “Provisioning data analytic workloads in a cloud,” Future Generation Computer Systems (FGCS), vol. 29, no. 6, 2013, pp. 1452–1458.
[6]    R. Mian, P. Martin, F. Zulkernine and J.L. Vazquez-Poletti, “Estimating Resource Costs of Data-intensive Workloads in Public Clouds,” 10th International Workshop on Middleware for Grids, Clouds and e-Science (MGC) in conjunction with ACM/IFIP/USENIX 13th International Middleware Conference 2012, ACM, 2012, article. 3, Montreal, QC, Canada.
[7]    R. Mian, P. Martin, A. Brown and M. Zhang, “Managing Data-Intensive Workloads in a Cloud,” Grid and Cloud Database Management, G. Aloisio and S. Fiore, eds., Springer, 2011.