Mohamed Gaber

Mohamed Gaber
Professor
Dean of Computer Science and Engineering

Bio

Professor Gaber is the Dean of Computer Science and Engineering. He received his PhD from Monash University, Australia, with an internship at IBM T. J. Watson Research Lab, USA.

Professor Gaber's research in Artificial Intelligence was funded by the Australian Research Council (ARC), and the EU Horizon 2020, among other sources. Professor Gaber has published over 200 papers, co-authored 3 monograph-style books and edited/co-edited 6 books on Artificial Intelligence.

According to the latest study conducted by Stanford University and Elsevier, and released in 2020. Professor Gaber is among the top 2% of the most cited scientists worldwide.

Qualifications

  • PhD from Monash University, Australia.

Publications

Area of Research

Artificial Intelligence: ensemble learning, learning from data streams, medical image analysis, natural language processing, time series classification, and deep learning


Link to Publications

Google-Scholar


List of Publications (Selected 50 out of more than 200 publications)

Authored Books

  1. Gaber M. M., Stahl F., and Gomes J., Pocket Data Mining: Big Data on Small Devices, Studies in Big Data Series, Volume 2, Springer Verlag, ISBN 978-3-319-02711-1, 2014.
  2. Edwards K. J., and Gaber M. M., Astronomy and Big Data: A Data Clustering Approach to Identifying Uncertain Galaxy Morphology, Studies in Big Data Series, Volume 6, Springer Verlag, ISBN 978-3-319-06599-1, 2014.

Edited Books

  1. Rehman M. H., and Gaber M. M. (Eds.), Federated Learning Systems: Towards Next-generation AI, Studiesin Computational Intelligence, Vol.  965, Springer Verlag, ISBN: 978-3-030-70604-3, 2021.
  2. Gaber M. M., Cocea M., Wiratunga N., and Goker A. (Eds.), Advances in Social Media Analysis, Studies in Computational Intelligence, Vol. 602, Springer Verlag, ISBN 978-3-319-18457-9, 2015.
  3. Gaber M. M. (Ed.), Journeys to Data Mining: Experiences from 15 Renowned Researchers, a book published by Springer Verlag, ISBN 978-3-642-28046-7, 2012.
  4. Gaber M. M. (Ed.), Scientific Data Mining and Knowledge Discovery: Principles and Foundations, a book published by Springer Verlag, ISBN 978-3-642-02787-1, 2009.
  5. Gama J., and Gaber M. M. (Eds.), Learning from Data Streams: Processing Techniques in Sensor Networks, a book published by Springer Verlag, ISBN 978-3-540-73678-3, 2007.

Journal Articles

  1. Abbas A., Abdelsamea M., and Gaber M. M., Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network, Applied Intelligence, Springer. [h5-index = 42, Impact Factor = 3.325]
  2. Dridi A., Gaber M. M., Azad R. M. A., and Bhogal J., Scholarly Data Mining: A Systematic Review of its Applications, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, Wiley press. [h5-index = 29, ranked 15th in top publications of Data Mining & Analysis, Impact Factor = 4.476].
  3. Hatwell J., Gaber M. M., and Azad R. M. A., gbt-HIPS: Explaining the Classifications of Gradient Boosted Tree Ensembles, Applied Sciences, MDPI. [h5-index = 53, ranked 17thin top publications of Physics & Mathematics(general), Impact Factor = 2.474]
  4. Hanga K., Kovalchuk Y., and Gaber M. M., A Graph-based Approach to Interpreting Recurrent Neural Networks in Process Mining, IEEE Access, IEEE press. [h5-index = 119, ranked 3rd in top publications of Engineering & Computer Science (general), Impact Factor = 3.745]
  5. Stahl F., Le T., Badii A., and Gaber M. M.,A Frequent Pattern Conjunction Heuristic for Rule Generation in Data Streams, Information, Volume 12, Issue 1, 2021, MDPI press. [h5-index = 28].
  6. Hatwell J., Gaber M. M., and Azad R. M. A., Ada-WHIPS: Explaining AdaBoost Classification with Applications in the Health Sciences, BMC Medical Informatics and Decision Making, Springer Nature. [h5-index = 41, ranked 7th in top publications of Medical Informatics, Impact Factor = 2.317]
  7. Abdallah Z. S., and Gaber M. M., Co-eye: A Multi-resolution Ensemble Classifier for Symbolically Approximated Time Series, Machine Learning, 109, pp. 2029–2061, Springer. [h5-index = 37, Impact Factor = 2.672]
  8. Abbas A., Abdelsamea M., and Gaber M. M., DeTraC: Transfer Learning of Class Decomposed Medical Images in Convolutional Neural Networks, IEEE Access, Volume 8, pp. 74901–74913, 2020, IEEE press. [h5-index = 119, ranked 3rd in top publications of Engineering & Computer Science (general), Impact Factor = 3.745]
  9. Hatwell J., Gaber M. M., and Azad R. M. A., CHIRPS: Explaining Random Forest Classification, Artificial Intelligence Review, Volume 53, Issue 8, pp. 5747–5788, 2020, Springer. [h5-index = 47, Impact Factor = 5.747]
  10. Fawagreh K., and Gaber M. M., Resource-efficient Fast Prediction in Healthcare Data Analytics: A Pruned Random Forest Regression Approach, Computing, Volume 102, pp. 1187–1198 Springer. [h5-index = 28, Impact Factor = 2.044]
  11. Ghomeshi H., Gaber M. M., and Kovalchuk Y., A Non-Canonical Hybrid Metaheuristic Approach to Adaptive Data Stream Classification, Future Generation Computer Systems, Volume 102, January 2020, pp. 127–139, Elsevier. [h5-index = 86, ranked 2nd in top publications of Computer Systems, Impact Factor = 5.768]
  12. Dridi A., Gaber M. M., Azad R. M. A., and Bhogal J., Leap2Trend: A Temporal Word Embedding Approach for Instant Detection of Emerging Scientific Trends, IEEE Access, Volume 7, pp. 176414–176428, 2019, IEEE press. [h5-index = 119, ranked 3rd in top publications of Engineering & Computer Science (general), Impact Factor = 3.745]
  13. Ghomeshi H., Gaber M. M., and Kovalchuk Y., RED-GENE: An Evolutionary Game Theoretic Approach to Adaptive Data Stream Classification, IEEE Access, Volume 7, pp. 173944–173954, 2019, IEEE press. [h5-index = 119, ranked 3rd in top publications of Engineering & Computer Science (general), Impact Factor = 3.745]
  14. Abdallah F., Basurra S., and Gaber M. M., A Non-intrusive Heuristic for Energy Messaging Intervention Modelled using a Novel Agent-based Approach, IEEE Access, Volume 7, pp. 1627–1646, 2019, IEEE press. [h5-index = 119, ranked 3rd in top publications of Engineering & Computer Science (general), Impact Factor = 3.745, winner of the 2018 IEEE Access Best Multimedia Award – Part 2].
  15. Ghomeshi H., Gaber M. M., and Kovalchuk Y., EACD: Evolutionary Adaptation to Concept Drifts in Data Streams, Data Mining and Knowledge Discovery, Volume 33, Issue 3, pp. 663–694, 2019, Springer-Verlag. [h5-index = 37, ranked 10th in top publications of Data Mining & Analysis, Impact Factor = 2.629]
  16. Gaber M. M., Aneiba A., Basurra S., Batty O., Elmisery A., Kovalchuk Y., and Habib ur Rehman M. Internet of Things and Data Mining: From Applications to Techniques and Systems, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, Volume 9, Issue 3, May/June 2019, e12922019. [h5-index = 29, ranked 15th in top publications of Data Mining & Analysis, Impact Factor = 4.476].
  17. Cuzzocrea A., Gaber M. M., Fadda E., Grasso G. M., An Innovative Framework for Supporting Big Atmospheric Data Analytics via clustering-based Spatio-temporal Analysis, Journal of Ambient Intelligence and Humanized Computing, pp. 1–16, 2018, Springer. [h5-index = 40, Impact Factor = 4.594].
  18. Demaidi M. N., Gaber M. M., and Filer N., OntoPeFeGe: Ontology-based Personalised Feedback Generator, IEEE Access, Volume 6, pp. 31644–31664, 2018, IEEE press. [h5-index = 119, ranked 3rd in top publications of Engineering & Computer Science (general), Impact Factor = 3.745].
  19. Abdallah Z. S., Gaber M. M., Srinivasan B., and Krishnaswamy S., Activity Recognition with Evolving Data Streams: A Review, ACM Computing Surveys (CSUR), Volume 51 Issue 4, July 2018, ACM press. [h5-index = 90, ranked 9th in top publications of Engineering & Computer Science (general), Impact Factor = 5.55].
  20. Hussein A., Elyan E., Gaber M. M.,and Jayne C., Deep Imitation Learning for 3D Navigation Tasks, Neural Computing and Applications, Volume 29 Issue 7, pp. 389–404, 2018, Springer. [h5-index = 67, ranked 14th in top publications of Artificial Intelligence, Impact Factor = 4.774]
  21. Yazici M. T. Basurra S., Gaber M. M., Edge Machine Learning: Enabling Smart Internet of Things Applications, Big Data and Cognitive Computing, MDPI press. [Editor’s Choice Article as the excellent paper in 2018]
  22. Demaidi M., Gaber M. M., Filer N., Evaluating the Quality of the Ontology-based Auto-generated Questions, Smart Learning Environments, Volume 4, Issue 7, pp. 1–24, 2017, Springer. [h5-index = 17]
  23. Habib ur Rehman M., Jayaraman P. P., Malik S., Khan A., and Gaber M. M., RedEdge: A Novel Architecture for Big Data Processing in Mobile Edge Computing Environments, Journal of Sensor and Actuator Networks, 2017, Volume 6, Issue 3, 17, MDPI press. [h5-index = 19, contributed to h5-index [2015–2020] ranked the 16th most cited paper]
  24. 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. [h5-index = 100, ranked 8th in top publications of Artificial Intelligence, Impact Factor = 4.438]
  25. Hussein A., Gaber M. M., Elyan E., and Jayne C., Imitation Learning: A Survey of Learning Methods, ACM Computing Surveys (CSUR), Volume 50 Issue 2, April 2017, ACM press. [h5-index = 90, ranked 9th in top publications of Engineering & Computer Science (general), Impact Factor = 5.55, contributed to h5-index [2015–2020] ranked the 41st most cited paper]
  26. Elyan E., and Gaber M. M., A Genetic Algorithm Approach to Optimising Random Forests Applied to Class Engineered Data, Information Sciences, Volume 384, April 2017, pp. 220–234, Elsevier. [h5-index = 102, ranked 5th in top publications of Engineering & Computer Science (general), Impact Factor = 5.910]
  27. Abdelsamea M. 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. [h5-index = 60, ranked 3rd in top publications of Evolutionary Computation, and 4th in top publications of Fuzzy Systems, Impact Factor = 3.050]
  28. Elyan E., and Gaber M. M., A Fine-Grained Random Forests using Class Decomposition: An Application to Medical Diagnosis, Neural Computing and Applications, November 2016, Volume 27, Issue 8, pp. 2279–2288, Springer. [h5-index = 67, ranked 14th in top publications of Artificial Intelligence, Impact Factor = 4.774].
  29. 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. [h5-index = 111, ranked 5th in top publications of Artificial Intelligence, Impact Factor = 5.452]
  30. 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. [h5-index = 17, contributed to h5-index [2015–2020], ranked the 6th most cited paper ]
  31. 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. [h5index = 100, ranked 8th in top publications of Artificial Intelligence, Impact Factor = 4.438]
  32. Abdelsamea M. 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. [h5-index = 100, ranked 8th in top publications of Artificial Intelligence, Impact Factor = 4.438]
  33. 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, Lecture Notes in Computer Science, Vol. 9070, pp. 90–107, Springer-Verlag.
  34. Fawagreh K., Gaber M. M., and Elyan E., Random Forests: From Early Developments to Recent Advancements, Systems Science & Control Engineering, Volume 2, Issue 1, 2014, pp. 602–609, Taylor & Francis. [h5-index = 17, contributed to h5-index [2014–2019], ranked the 4th most cited paper]
  35. Gaber M. M., Gama J., Krishnaswamy S., Gomes J., and Stahl F., Data Stream Mining in Ubiquitous Environments: State-of-the-art and Current Directions, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, Volume 4, Issue 2, pp. 116–138, March/April 2014.[h5-index = 29, ranked 15th in top publications of Data Mining & Analysis, Impact Factor = 4.476, contributed to h5-index [2014–2019], ranked the 35th most cited paper].
  36. 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. [h5-index = 107, ranked 7th in top publications of Artificial Intelligence, Impact Factor = 8.793]
  37. Gomes J. B., Gaber M. M., Sousa P., and Menasalvas E., Collaborative Data Stream Mining in Ubiquitous Environments using Dynamic Classifier Selection, International Journal of Information Technology & Decision Making, Volume 12, Issue 06, November 2013, World Scientific Publishing Company. [h5-index = 24, ranked 11th in top publications in Fuzzy Systems, Impact Factor = 1.894 ]
  38. Gaber M. M., Krishnaswamy S., Gillick B., AlTaiar H., Nicoloudis N., Liono J., and Zaslavsky A., Interactive Self Adaptive Clutter-Aware Visualisation for Mobile Data Mining, Journal of Computer and System Sciences, Volume 79 Issue 3, May 2013, pp. 369-382. Elsevier. [h5-index = 31, ranked 9th in top publications of Theoretical Computer Science, Impact Factor = 1.494]
  39. Gaber M. M., Advances in Data Stream Mining, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, Volume 2 (1), pp. 79-85, 2012. [h5-index = 29, ranked 15th in top publications of Data Mining & Analysis, Impact Factor = 4.476].
  40. Chong S. K., Gaber M. M., Krishnaswamy S., and Loke S. W., Energy Conservation in Wireless Sensor Networks: A Rule-based Approach, Knowledge and Information Systems (KAIS) Journal, Volume 28, Number 3, pp. 579–614, ISSN 0219-1377, Springer London, 2011. [h5-index = 43, ranked 7th in top publications of Data Mining & Analysis, and 12th in top publications of Databases & Information Systems, Impact Factor = 2.936]
  41. Gaber M. M., Roehm U., and Herink K., An Analytical Study of Central and In-network Data Processing for Wireless Sensor Networks, Information Processing Letters, Elsevier, Volume 110, Number 2, pp. 62-70, December 2009. [h5-index = 26, ranked 16th in top publications in Theoretical Computer Science, Impact Factor = 0.677]
  42. Gaber M. M., and Yu P. S., A Holistic Approach for Resource-aware Adaptive Data Stream Mining, Journal of New Generation Computing, ISSN 0288-3635 (Print) 1882-7055 (Online), Volume 25, Number 1, November, 2006, pp. 95-115, Ohmsha, Ltd., and Springer Verlag.[h5-index = 12, Impact Factor = 0.889]
  43. Gaber M. M., and Yu P. S., Detection and Classification of Changes in Evolving Data Streams, International Journal of Information Technology & Decision Making, Vol. 5, No. 4, pp. 659-670, World Scientific Publishing Company, 2006. [h5-index = 24, ranked 11th in top publications in Fuzzy Systems, Impact Factor = 1.894]

Awards & Honorable Mentions

  • Listed in the top 2% of researchers globally, according to a comprehensive study by Elsevier and Stanford University released in 2020.
  • Fellow of the Higher Education Academy (HEA), United Kingdom: prepared a successful fellowship application for the recognition by the Higher Education Academy in the United Kingdom (recognized since 2011).
  • Australian Postdoctoral Fellowship: awarded the prestigious and nationally competitive Australian Postdoctoral (APD) Fellow (only 120 early career researchers nationwide awarded the APD to commence the fellowship in 2008).
  • CSIRO Teamwork Award: awarded the Commonwealth Scientific and Industrial Research Organisation (CSIRO) teamwork award in 2007


Best Paper Awards

  • Promotional Prize Winner for the 2018 IEEE Access Best Multimedia Award Part 2 for the multimedia submitted with our article entitled, “A Non-intrusive Heuristic for Energy Messaging Intervention Modelled using a Novel Agent-based Approach".
  • Editor's Choice Article: chosen as the excellent paper in 2018 for our article titled “Edge Machine Learning: Enabling Smart Internet of Things Applications" published in the Big Data and Cognitive Computing journal.

Best Student Paper Award

  • Awarded for our paper titled “An Agent-Based Collective Model to Simulate Peer Pressure Effect on Energy Consumption" published in the Proceedings of 10th International Conference on Computational Collective Intelligence, (ICCCI 2018), with the completed PhD student (Dr Fatima Abdallah).

Best Paper Award

  • Awarded for our paper titled “Reliable and Energy Efficient Backup Clustering Scheme for Wireless Sensor Networks" published in the Proceedings of the International on Information Networking (ICOIN 2010).

Supervision

Professor Gaber has supervised/co-supervised to successful completion 14 PhD students. He has acted as an examiner for 28 PhD candidates in the United Kingdom, the Netherlands, Australia, New Zealand, Mauritius, Malaysia, Pakistan, India, Germany, and Portugal.

Activities

  • General co-chair of the 3rd IEEE International Conference on Data Science and Computational Intelligence (DSCI 2019) and
  •  The programme committee co-chair of the IEEE Mobile Data Management (MDM 2016), among the many other events. 
  • Served in the program committees of major conferences related to data mining, including ICDM, PAKDD, ECML/PKDD and ICML. 
  • Recognized as a Fellow of the British Higher Education Academy (HEA).

Hurry to apply for a promising future.

Seize the opportunity to be unique across the first-ever smart university's campus in Egypt.

LET`S CONNECT

Video Conference

Zoom: Guofficial2020@gmail.com

Mail

info@gu.edu.eg

Campus Location

Galala Plateau , Attaka , Suez

SEND US A MESSAGE


    WE ARE HERE

    Connect with us!

    If you Have Any Questions Call Us On (010)123-456-7890