Dr Essam Debie

Research Associate
School of Engineering and Information Technology
+61 2 6268 8191
  • ABOUT
  • PUBLICATIONS

Essam earned a Ph.D. in Computer Science in 2014, a M.Sc. degree in Information Systems in 2010 and a B.Sc. in Information Systems and Technology in 2003.

Currently, Essam is a Postdoctoral Research Fellow with the School of Engineering and Information Technology, University of New South Wales Canberra. His research interests are concentrated on Data Mining, Machine Learning, Cognitive Computing, and Trusted Autonomy.

 

Grants

  1. E. Debie (2018) NVIDIA GPU Grant (Nvidia Quadro P6000 graphics card), US$7,000.

Journal articles

Debie E; Fernandez Rojas R; Fidock J; Barlow M; Kasmarik K; Anavatti S; Garratt M; Abbass H, 2019, 'Multi-Modal Fusion for Objective Assessment of Cognitive Workload: A Review', IEEE Transactions on Cybernetics

Shafi K; Debie E; Oliver D, 2018, 'Historical operational data analysis for defence preparedness planning', Journal of Defense Modeling and Simulation, vol. 15, pp. 231 - 244, http://dx.doi.org/10.1177/1548512916664803

Debie E; Shafi K, 2017, 'Implications of the curse of dimensionality for supervised learning classifier systems: theoretical and empirical analyses', Pattern Analysis and Applications, pp. 1 - 18, http://dx.doi.org/10.1007/s10044-017-0649-0

Debie E; Shafi K; Merrick K; Lokan C, 2017, 'On Taxonomy and Evaluation of Feature Selection-Based Learning Classifier System Ensemble Approaches for Data Mining Problems', Computational Intelligence, vol. 33, pp. 554 - 578, http://dx.doi.org/10.1111/coin.12099

Merrick K; Debie E; Shafi K; Lokan C, 2013, 'Performance Analysis of Rough Set Ensemble of Learning Classifier Systems with Differential Evolution based Rule Discovery', Evolutionary Intelligence, vol. 6, pp. 109 - 126, http://dx.doi.org/10.1007/s12065-013-0093-z

Conference Papers

Nguyen T; Nguyen H; Debie E; Kasmarik K; Garratt M; Abbass H, 2018, 'Swarm Q-Learning With Knowledge Sharing Within Environments for Formation Control', in Proceedings of the International Joint Conference on Neural Networks, International Joint Conference on Neural Networks, Brazil, presented at International Joint Conference on Neural Networks, Brazil, - , http://dx.doi.org/10.1109/IJCNN.2018.8489674

Debie E; Elsayed SM; Essam DL; Sarker RA, 2016, 'Investigating multi-operator differential evolution for feature selection', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 273 - 284, http://dx.doi.org/10.1007/978-3-319-28270-1_23

Debie E; Shafi K; Merrick K; Lokan CJ, 2014, 'An Online Evolutionary Rule Learning Algorithm with Incremental Attribute Discretization', in 2014 IEEE Congress on Evolutionary Computation (CEC), IEEE, Beijing, China, pp. 1116 - 1123, presented at IEEE Congress on Evolutionary Computation, Beijing, China, 06 July 2014 - 11 July 2014, http://dx.doi.org/10.1109/CEC.2014.6900623

debie E; shafi K; Lokan CJ; merrick K, 2013, 'Reduct Based Ensemble of Learning Classifier System for Real-valued Classification Problems', in Pal NR; Yao X; Suganthan PN (eds.), Proceedings 2013 IEEE Symposium on Computational Intelligence and Ensemble Learning (CIEL 2013), Singapore, pp. 66 - 73, presented at 2013 IEEE Symposium on Computational Intelligence and Ensemble Learning, Singapore, 16 April 2013 - 19 April 2013, http://dx.doi.org/10.1109/CIEL.2013.6613142

Debie E; Shafi K; Lokan CJ; Merrick K, 2013, 'Investigating Differential Evolution Based Rule Discovery in Learning Classifier Systems', in Brest J; Das S; Neri F; Suganthan PN (eds.), Proceedings of the 2013 IEEE Symposium on Differential Evolution, SDE 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013, Singapore, pp. 77 - 84, presented at 2013 IEEE Symposium on Differential Evolution, Singapore, 16 April 2013 - 19 April 2013, http://dx.doi.org/10.1109/SDE.2013.6601445

Debie E; Shafi K; Lokan C, 2013, 'REUCS-CRG: Reduct based ensemble of supervised classifier system with combinatorial rule generation for data mining', in GECCO 2013 - Proceedings of the 2013 Genetic and Evolutionary Computation Conference Companion, pp. 1251 - 1258, http://dx.doi.org/10.1145/2464576.2482703

Shafi K; Merrick K; Debie E, 2012, 'Evolution of Intrinsic Motives in Multi-agent Simulations', in Lecture Notes in Computer Science (LNCS), Springer, pp. 198 - 207, presented at The Ninth International Conference on Simulated Evolution and Learning, 16 December 2012 - 19 December 2012, http://dx.doi.org/10.1007/978-3-642-34859-4_20