Dr Faiza Samreen BCS(Hons), MS, PhD
- Department of Computing
- Communication and Computing Research Centre
- Industry and Innovation Research Institute
Dr. Faiza Samreen is a senior lecturer in Smart Computing at Sheffield Hallam University. She is a proactive lecturer and researcher with over ten years of research and academic experience. Faiza’s prime research focus is related to applied machine learning and distributed systems, emphasizing cloud computing. As a researcher, she values the importance of interdisciplinary work and is always intrigued to work with other subject disciplines. Dr. Samreen is interested in investigating the new and emerging technologies from distributed systems and machine learning paradigm that can help scientists support scientiﬁc research in various ways.
Dr. Samreen is a very active researcher with over ten years of experience serving national and international institutes. For the past seven years she has been researching distributed systems with a particular emphasis on the conﬂuence of cloud computing and machine learning and how they can work together addressing real world problems. The focus of her Ph.D. work was designing and developing a machine learning-assisted decision support system for cloud customers. After completing her Ph.D., she worked as a Senior Research Associate on an EPSRC funded multidisciplinary research project at the School of Computing and Communications, Lancaster University. During the tenure, she designed and developed a framework to deploy largescale simulations on a cloud platform. This framework oﬀered a collaborative and reproducible environment to climate scientists and enabled democratised access of this model for the wider community. This research work has been extended at LU to investigate the role of machine learning in capturing the internal model variability of Weather and Research Forecasting model. She is still associated with Lancaster University as a visiting researcher and working with the Ensemble team.
As an author and co-author, she has 14 publications to her name. These have been published in high-impact journals and conferences, such as, IEEE Transaction on Cloud Computing, Journal of Environmental Modelling and Software, ACM Computing Surveys, IEEE/IFIP NOMS, ICSE. She has nine abstracts accepted in diﬀerent venues of the environmental science community and has presented her work in various seminars, conferences, and summits nationally and internationally. Dr. Samreen is a successful grantee of two educational and research grants from two public cloud providers, Amazon Web Services and Microsoft Azure AI for Earth.
She has also served as a Technical Programme Committee UCU Doctoral Symposium member 2020, CrossCloud18-19, keynote chair for CrossCloud17, reviewer for Journal of Internet Services and Applications, Springer Open Journal, 2015, 2017 and of 8th International ACM WebScience Conference, 2016. Recently, she was invited as a guest speaker for the Azure in Education Webinar Series to share her experience working on Microsoft Azure Lab.
Dr. Samreen is a module leader and instructor for three modules. Her teaching philosophy is largely inﬂuenced by innovative and inclusive practices that support learning diversity, hence, enhancing the foundation for learning experiences for students and allowing them to ﬂourish and succeed.
College of Business, Technology and Engineering
BSc (Hons) Computing
BSc (Hons) Information Technology with Business Studies
BSc (Hons) Business and Digital Technology
Advanced System Architectures
Introduction to Cloud Computing
Computer Technology for Business
- A collaborative research work aiming at designing solutions for epidemiologists and focusing on the technological aspect of redesigning their models to beneﬁt from the digital innovations in data science and distributed systems. This work involves Dr. Gavin Abernethy (Engineering & Maths, SHU), Dr. Carlos Da Silva (Computing, SHU), Dr. Marjory Da Costa (Computing, SHU) and Dr. Sally Fowler Davis (AWRC).
- Investigate the role of machine learning in capturing the internal model variability of Weather and Research Forecasting model. This work involves environmental scientists from Lancaster University and supported by Microsoft Azure AI 4 Earth Grant. https://www.ensembleprojects.org/
Dr. Gavin Abernethy (Engineering & Maths, SHU)
Dr. Carlos Da Silva (Computing, SHU)
Dr. Marjory Da Costa (Computing, SHU)
Dr. Sally Fowler Davis (AWRC)
Prof. Gordon S. Blair (Lancaster University)
Dr. Will Simm (Lancaster University)
Dr. Richard Bassett (Lancaster University)
Samreen, F., Blair, G., & Elkhatib, Y. (2020). Transferable knowledge for Low-cost Decision Making in Cloud Environments. IEEE Transactions on Cloud Computing. http://doi.org/10.1109/TCC.2020.2989381
Blair, G.S., Bassett, R., Bastin, L., Beevers, L., Borrajo, M.I., Brown, M., ... Watkins, J. (2021). The Role of Digital Technologies in Responding to the Grand Challenges of the Natural Environment: The Windermere Accord. Patterns, 2 (1). http://doi.org/10.1016/j.patter.2020.100156
Bassett, R., Young, P.J., Blair, G.S., Samreen, F., & Simm, W. (2020). The megacity Lagos and three decades of urban heat island growth. Journal of Applied Meteorology and Climatology, 59 (12), 2041-2055. http://doi.org/10.1175/jamc-d-20-0059.1
Bassett, R., Young, P.J., Blair, G.S., Samreen, F., & Simm, W. (2020). A Large Ensemble Approach to Quantifying Internal Model Variability Within the WRF Numerical Model. Journal of Geophysical Research: Atmospheres, 125 (7). http://doi.org/10.1029/2019jd031286
Blair, G.S., Beven, K., Lamb, R., Bassett, R., Cauwenberghs, K., Hankin, B., ... Towe, R. (2019). Models of everywhere revisited: A technological perspective. Environmental Modelling & Software, 122, 104521. http://doi.org/10.1016/j.envsoft.2019.104521
Blair, G., Beven, K., Lamb, R., Bassett, R., Cauwenberghs, K., Hankin, B., ... Towe, R. (2019). Models of everywhere revisited: a technological perspective. Environmental Modelling and Software, 122, 104521. http://doi.org/10.1016/j.envsoft.2019.104521
Elhabbash, A., Samreen, F., Hadley, J., & Elkhatib, Y. (2019). Cloud Brokerage: A Systematic Survey. ACM Computing Surveys, 51 (6), 1-28. http://doi.org/10.1145/3274657
Samreen, F., Simm, W., Blair, G., Bassett, R., & Young, P. (2020). Models in the Cloud: Exploring Next Generation Environmental Software Systems. In International Symposium on Environmental Software System, Netherland, 5 February 2020 - 7 February 2020. Springer, Cham: https://link.springer.com/chapter/10.1007%2F978-3-030-39815-6_21
Elkhatib, Y., Samreen, F., & Blair, G. (2019). Same Same, but Different: A Descriptive Intra-IaaS Differentiation. 2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID). http://doi.org/10.1109/ccgrid.2019.00089
Simm, W.A., Samreen, F., Bassett, R., Ferrario, M.A., Blair, G., Whittle, J., & Young, P.J. (2018). SE in ES: opportunities for software engineering and cloud computing in environmental science. Proceedings of the 40th International Conference on Software Engineering Software Engineering in Society - ICSE-SEIS '18, 61-70. http://doi.org/10.1145/3183428.3183430
Samreen, F., Elkhatib, Y., Rowe, M., & Blair, G.S. (2016). Daleel: simplifying cloud instance selection using machine learning. NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium. http://doi.org/10.1109/noms.2016.7502858
Samreen, F., Blair, G.S., & Rowe, M. (2014). Adaptive decision making in multi-cloud management. Proceedings of the 2nd International Workshop on CrossCloud Systems. http://doi.org/10.1145/2676662.2676676