Biography

Mohamed is a Professor in Data Analytics at the School of Computing and Digital Technology, Birmingham City University. Mohamed received his PhD from Monash University, Australia. He then held appointments with the University of Sydney, CSIRO, and Monash University, all in Australia. Prior to joining Birmingham City University, Mohamed worked for the Robert Gordon University as a Reader in Computer Science and at the University of Portsmouth as a Senior Lecturer in Computer Science, both in the UK. He has published over 150 papers, co-authored 2 monograph-style books, and edited/co-edited 6 books on data mining and knowledge discovery. His work has attracted well over three thousand citations, with an h-index of 31. Mohamed has served in the program committees of major conferences related to data mining, including ICDM, PAKDD, ECML/PKDD and ICML. He has also co-chaired numerous scientific events on various data mining topics. Professor Gaber is recognised as a Fellow of the British Higher Education Academy (HEA). He is also a member of the International Panel of Expert Advisers for the Australasian Data Mining Conferences. In 2007, he was awarded the CSIRO teamwork award. 

A more interesting biography

Picture
I was born a few miles away from the Pyramids in Cairo, Egypt. I received my PhD from Monsah University in Melbourne, the first capital (temporarily) of Australia.  During my PhD, I did an internship at IBM Thomas J. Watson, where the relational database model was invented by Edgar F. Codd. After my PhD, I held research positions at the University of Sydney, the oldest/first Australian University which is located close to where Captain James Cook first landed in Australia; CSIRO in Hobart, the capital of Tasmania: the only Australian state out of the Australian mainland; and back to Monash University when awarded the prestigious Australian Postdoctoral Fellowship. I worked as a senior lecturer in computer science at the University of Portsmouth, where Charles Dickens was born. I then moved to the oil Capital of Europe and the Granite City, Aberdeen, to take up the position of Reader in computer science at Robert Gordon University. Most recently, in Birmingham, the first manufacturing town in the world, I became a Full Professor in data analytics at Birmingham City University.
By the words of the great poet, Hafez Ibrahim, the legend Umm Kulthum sang: "..and the builders of the pyramids in the ancient age sufficed me the talk when challenged". Listen to great music and song

Research Contribution Map

Publications

(Ten) Recent/Representative Publications

  • Abdallah Z. S., Gaber M. M., Srinivasan B., and Krishnaswamy S., Activity Recognition with Evolving Data Streams: A Review, ACM Computing Surveys (CSUR), ACM press, in press. [DOI]
  • Le T., Stahl F., Gaber M. M., Gomes J. B., and Di Fatta G., On Expressiveness and Uncertainty Awareness in
    Rule-based Classification for Data Streams    , Neurocomputing,Volume 265, 22 November 2017, pp. 127-141 Elsevier. [DOI]
  • Abdelsamea M., Gnecco G., and Gaber M. M., A SOM-based Chan-Vese Model for Unsupervised Image Segmentation, Soft Computing, April 2017, Volume 21, Issue 8, pp 2047–2067, Springer. [DOI]
  • Abdallah Z. S., Gaber M. M., Srinivasan B., and Krishnaswamy S., AnyNovel: Detection of Novel Concepts in Evolving Data Streams, Evolving Systems, June 2016, Volume 7, Issue 2, pp. 73-93, Springer. [DOI]
  • Adedoyin-Olowe M., Gaber M. M., Martin-Dancausa C., Stahl F., and Gomes J. B., A Rule Dynamics Approach to Event Detection in Twitter with Its Application to Sports and Politics, Expert Systems with Applications, Volume 55, 15 August 2016, pp. 351–360​, Elsevier. [DOI]
  • Abdallah Z. S., Gaber M. M., Srinivasan B., and Krishnaswamy S., Adaptive Mobile Activity Recognition System with Evolving Data Stream, Neurocomputing, Volume 150, Part A, 20 February 2015, pp. 304-317, Elsevier. [DOI]
  • Abdelsamea M., Gnecco G., and Gaber M. M., An Efficient Self Organizing Active Contour Model for Image Segmentation, Neurocomputing, Volume 149, Part B, 3 February 2015, pp. 820-835,Elsevier. [DOI]
  • Stahl F., May D., Mills H., Bramer M., and Gaber M. M., A Scalable Expressive Ensemble Learning using Random Prism: A MapReduce Approach, Transactions on Large-Scale Data- and Knowledge-Centered Systems XX,  LNCS 9070, pp. 90-107, Springer-Verlag, 2015. [DOI]​
  • Gaber, M. M., Gama J., Krishnaswamy S., Gomes J. B., and Stahl F., Data Stream Mining in Ubiquitous Environments: State‐of‐the‐art and Current Directions, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 4(2),  pp. 116-138, March/April 2014. [DOI]
  • Gomes J. B., Gaber M. M., Menasalvas E., and Sousa P., Mining Recurring Concepts in a Dynamic Feature Space, IEEE Transactions on Neural Networks and Learning Systems, Volume 25, Issue 1, pp. 95-110, January 2014. [DOI]

List of Publications

Books

According to Google Scholar in April 2018

Citation count: 3,671     
h-index: 31       g-index: 55       i10-index:  74       
Erdos number: 4     RG Score: 29+        

The above graph is generated using the R package "scholar" in November 2013. The calculations are based on the following paper: 

D E Acuna, S Allesina, K P Kording (2012) Future impact: Predicting scientific success. Nature 489, pp. 201-202. 

Demonstrations
Since March, 2014
Flag Counter