•  Zahraa Said Abdallah, Mohamed Medhat Gaber, Bala Srinivasan, and Shonali Krishnaswamy. StreamAR: Incremental and active learning with evolving sensory data for activity recognition. In Proceedings of the IEEE International Conference on Tools with Articial Intelligence , Nov 2012, Athens, Greece (ICTAI 2012). pdf

  • Zahraa Said Abdallah, Mohamed Medhat Gaber, Bala Srinivasan, and Shonali Krishnaswamy. CBARS: Cluster based classication for activity recognition systems. In Proceedings of the International Conference on Advanced Machine Learning Technologies and Applications, Lecture Notes in Computer Science. Springer, Dec 2012, Cairo, Egypt (AMLTA12). pdf

  • Zahraa Said Abdallah and Mohamed Medhat Gaber. A Novel Ensemble Similarity-based Approach to Machine Learning.  International Journal of Information Technology & Decision Making. Accepted, subject to final revision.

  • Andrey Boytsov, Arkady B. Zaslavsky, and Zahraa Abdallah. Where have you been? using location clustering and context awareness to understand places of interest. In Sergey D.Andreev, Sergey Balandin, and Yevgeni Koucheryavy, editors NEW2AN, volume 7469 of Lecture Notes in Computer Science, pages 51-62. Springer, July 2012. pdf

  •  Zahraa Said Abdallah,Shonali Krishnaswamy,Bala Srinivasan and Mohamed Medhat Gaber. Mobile Activity Recognition Using Contextual Reasoning and Ubiquitous Data Stream Processing.  Australasian Computing Doctoral Consortium 2012, (ACDC'12). pdf

  •  Zahraa Said Abdallah and Mohamed Medhat Gaber. KB-CB-N classification: Towards unsupervised approach for supervised learning. In Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2011, part of the IEEE Symposium Series on Computational Intelligence, pages 283- 290, 2011. pdf 

  • Zahraa Said Abdallah and Mohamed Medhat Gaber. DDG-clustering: A novel technique for highly accurate results.  In Proceedings of the IADIS European Conference on Data Mining, pages 163-167, 2009, ( IADIS 2009). pdf 


  • Ranked first in OPPORTUNITY Activity Recognition Challenge. OPPORTUNITY is a FET-Open (Future and Emerging Technologies Open Call) project under the Information and Communication Technologies theme of the 7th Framework Program of the European Commission Handte et al. (2010). 



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