I have over 15 years of research and development experience with both industry and academia. I have worked in many roles with Higher Education, as a Lecturer, Programme Leader, Research Fellow and my current role as Academic Lead in Computing and IT.

I am also have ’Senior Member IEEE’ status. IEEE is the world's largest technical professional organisation for the advancement of technology with over 400,00 members. This member status requires extensive experience, reflects professional maturity and documented achievements of significance and only 10% of its members hold this membership grade.

Your Thoughts About Online Learning

Online learning reduces barriers to learning and provides opportunity to students to continue their studies without a major disruption to their personal and professional lives. It inspires me to be creative with my teaching material and delivery methods. Furthermore, it enables me deliver the most up to date knowledge to the students in response to the industry needs in real time.


Professional Memberships

Senior Member IEEE


PhD Computer Science, Delft University of Technology

Past Projects include:

Stream Cloud: I worked as a KTP associate on this project to develop an end-to-end solution for batch and real time analysis of video streams using cloud computing. Image processing algorithms were ported to GPUs for reducing video stream processing time and costs. Machine learning algorithms are applied to search, recognise and compare objects, and track and to monitor the objects under a controlled environment. Profiles were created to find patterns and events or unusual behaviours in video streams.

Genomics Data Analyser: Recent advances in genomic sequencing technology have led to a dramatic reduction in genome sequencing costs, paving the way for large-scale sequencing projects. The longenvisioned prospects of personalised diagnosis and treatment of disease could soon be a reality.

In this project, we implemented an approach that combines both powerful efficient processing of big genomics data with scalable data storage. Apache Spark’s powerful parallel in-memory processing approach is combined Apache HBase to deliver a high-performance analytics tool that can efficiently scale with increasing genomic data sets. A population clustering algorithm on genomics datasets is implemented to demonstrate the effectiveness of our approach.

Disease Registry Miner: A cloud based, text mining tools for finding/extracting/analysing disease registries from millions of research articles and web pages and applies machine learning algorithms.

Metadata Repository: Capture and store metadata from a data warehouse and the data stored in HDFS f for maintaining the integrity/governance. I was involved in the analysis and design of this project.


Journal/Book Chapters:

1. Ashiq Anjum, Tariq Abdullah, Faheem Tariq, Yusuf Baltaci, Nick Antonopoulos, "Video Stream Analysis in Clouds: An Object Detection and Classification Framework for High Performance Video Analytics”, IEEE Transactions on Cloud Computing, 2016.

2. Ashiq Anjum, Sanna Aizad, Bilal Arshad, Moeez Subhani, Dominic Davies-Tagg, Tariq Abdullah, and Nick Antonopoulos, " Big Data Analytics in Healthcare: A Cloud based Framework for Generating Insights”, Cloud Computing: Principles, Systems and Applications, 2016


3. Tariq Abdullah, Ahmed Ahmet, "Genomics Analyser: A Big Data Framework for Analysing Genomics Data", IEEE/ACM 4th International Conference on Big Data Computing, Applications and Technologies (BDCAT), 2017, Austin, Texas, USA[Accepted for publication].

4. Tariq Abdullah, Ashiq Anjum, Faheem Tariq, Yusuf Baltaci, Nick Antonopoulos, "Traffic Monitoring Using Video Analytics in Clouds", IEEE/ACM 7th International Conference on Utility and Cloud Computing (UCC), 2014, London UK. IA Number: 14888433, Page(s): 39 - 48, DOI: 10.1109/UCC.2014.12 [Winner of 2nd Best Paper Award]

5. Tariq Abdullah, Ashiq Anjum, Nik Bessis, Stelios Sotiriadis, Koen Bertels, "Nature Inspired Self organization for Ad Hoc Grids", The 27th IEEE International Conference on Advanced Information Networking and Applications,25-28 March 2013 Barcelona, Spain Pages: 682 - 689, ISSN: 1550- 445X, ISBN: 978-1-4673-5550-6 DOI: 10.1109/ AINA.2013.144

6. Tariq Abdullah, K.L.M. Bertels, "Nature-inspired self-organization in P2P Ad Hoc grids", 7th International Conference on Autonomic and Autonomous Systems (ICAS), pages 134-139, Mestre, Italy, May 2011.

7. Tariq Abdullah, Koen Bertels, Luc Onana Alima, Zubair Nawaz, "Effect of Degree of Neighborhood on resource discovery in Ad Hoc Grids", 23nd International Conference on Architecture of Computing Systems, February 2010.

8. Tariq Abdullah, Koen. Bertels, Luc Onana Alima, "Ant Colony Inspired Microeconomic based Resource Management in Ad Hoc Grids", 4th International Conference on Grid and Pervasive Computing, Geneva, May 2009.

9. Tariq Abdullah, Luc Onana Alima, Vassilly Sokolov, David Calomme, Koen Bertels, "Hybrid Resource Discovery Mechanism in Ad Hoc Grid Using Structured Overlay", 22nd International Conference on Architecture of Computing Systems, March 2009.

10. Tariq Abdullah, Lotfi Mhamdi, Behnaz Pourebrahimi, Koen. Bertels, "Resource Discovery with Dynamic Matchmakers in Ad Hoc Grid", The Fourth International Conference on Systems, March 2009.

11. Tariq Abdullah, Koen. Bertels, "Agent Toolkits for Ad Hoc Grids", 32nd International Conference on Artificial Intelligence Workshops, Paderborn, September 2009

12. Tariq Abdullah, Vassilly Sokolov, Behnaz Pourebrahimi, Koen Bertels, "Self-Organizing Dynamic Ad Hoc Grids", In Proceedings of 2nd IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshops (SASOW 2008), Venice, October 2008.


Research Interests

  • Distributed Systems
  • Big data and Data Analytics
  • Intelligent Systems
  • Business Analytics