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Dr Essam Debie
Post-Doc Fellow

Dr Essam Debie

 

UNSW Canberra
School of Systems & Computing

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.

E-mail
e.debie@adfa.edu.au
  • Book Chapters | 2021
    Debie E; Fernandez Rojas R; fidock J; Barlow M; Kasmarik K; Anavatti S; Garratt M; Abbass H, 2021, 'Transparent Shepherding: A Rule-Based Learning Shepherd for Human Swarm Teaming', in Shepherding UxVs for Human-Swarm Teaming An Artificial Intelligence Approach to Unmanned X Vehicles, Springer Nature, pp. 267 - 292, http://dx.doi.org/10.1007/978-3-030-60898-9_12
    Book Chapters | 2021
    Fernandez Rojas R; Debie E; fidock J; Barlow M; Kasmarik K; Anavatti S; Garratt M; Abbass H, 2021, 'Human Performance Operating Picture for Shepherding a Swarm of Autonomous Vehicles', in Shepherding UxVs for Human-Swarm Teaming An Artificial Intelligence Approach to Unmanned X Vehicles, Springer Nature, pp. 293 - 323, http://dx.doi.org/10.1007/978-3-030-60898-9_13
    Book Chapters | 2016
    Debie E; Elsayed SM; Essam DL; Sarker RA, 2016, 'Investigating multi-operator differential evolution for feature selection', in , pp. 273 - 284, http://dx.doi.org/10.1007/978-3-319-28270-1_23
  • Journal articles | 2023
    Debie E; Kasmarik K; Garratt M, 2023, 'Swarm Robotics: A Survey from a Multi-Tasking Perspective', ACM Computing Surveys, 56, http://dx.doi.org/10.1145/3611652
    Journal articles | 2022
    Debie E; Moustafa N; Vasilakos A, 2022, 'Session Invariant EEG Signatures using Elicitation Protocol Fusion and Convolutional Neural Network', IEEE Transactions on Dependable and Secure Computing, 19, pp. 2488 - 2500, http://dx.doi.org/10.1109/TDSC.2021.3060775
    Journal articles | 2021
    Debie E; El-Fiqi H; Fidock J; Barlow M; Kasmarik K; Anavatti S; Garratt M; Abbass H, 2021, 'Autonomous recommender system for reconnaissance tasks using a swarm of UAVs and asynchronous shepherding', Human-Intelligent Systems Integration, 3, pp. 175 - 186, http://dx.doi.org/10.1007/s42454-020-00024-w
    Journal articles | 2021
    Hepworth AJ; Baxter DP; Hussein A; Yaxley KJ; Debie E; Abbass HA, 2021, 'Human-Swarm-Teaming Transparency and Trust Architecture', IEEE/CAA Journal of Automatica Sinica, 8, pp. 1281 - 1295, http://dx.doi.org/10.1109/JAS.2020.1003545
    Journal articles | 2020
    Asharf J; Moustafa N; Khurshid H; Debie E; Haider W; Wahab A, 2020, 'A review of intrusion detection systems using machine and deep learning in internet of things: Challenges, solutions and future directions', Electronics (Switzerland), 9, http://dx.doi.org/10.3390/electronics9071177
    Journal articles | 2020
    Elsayed S; Singh H; Debie E; Perry A; Campbell B; Hunjel R; Abbass H, 2020, 'Path Planning for Shepherding a Swarm in a Cluttered Environment using Differential Evolution', 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020, pp. 2194 - 2201, http://dx.doi.org/10.1109/SSCI47803.2020.9308572
    Journal articles | 2020
    Fernandez Rojas R; Debie E; Fidock J; Barlow M; Kasmarik K; Anavatti S; Garratt M; Abbass H, 2020, 'Electroencephalographic Workload Indicators During Teleoperation of an Unmanned Aerial Vehicle Shepherding a Swarm of Unmanned Ground Vehicles in Contested Environments', Frontiers in Neuroscience, 14, http://dx.doi.org/10.3389/fnins.2020.00040
    Journal articles | 2019
    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
    Journal articles | 2018
    Shafi K; Debie E; Oliver D, 2018, 'Historical operational data analysis for defence preparedness planning', Journal of Defense Modeling and Simulation, 15, pp. 231 - 244, http://dx.doi.org/10.1177/1548512916664803
    Journal articles | 2017
    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, 33, pp. 554 - 578, http://dx.doi.org/10.1111/coin.12099
    Journal articles | 2017
    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
    Journal articles | 2013
    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, 6, pp. 109 - 126, http://dx.doi.org/10.1007/s12065-013-0093-z
  • Conference Papers | 2021
    Debie E; Singh H; Elsayed S; Perry A; Hunjet R; Abbass H, 2021, 'A Neuro-Evolution Approach to Shepherding Swarm Guidance in the Face of Uncertainty', in Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, pp. 2634 - 2641, http://dx.doi.org/10.1109/SMC52423.2021.9659082
    Conference Papers | 2020
    Debie E; Moustafa N; Whitty M, 2020, 'A Privacy-Preserving Generative Adversarial Network Method for Securing EEG Brain Signals', in IEEE World Congress on Computaional Intelligence (IEEE WCCI), 2020, IEEE, Glasgow, United kingdom, presented at IEEE World Congress on Computaional Intelligence (IEEE WCCI), 2020, Glasgow, United kingdom, 19 July 2020 - 24 July 2020
    Conference Papers | 2020
    Elsayed S; Singh H; Debie E; Perry A; Campbell B; Hunjel R; Abbass H, 2020, 'Path Planning for Shepherding a Swarm in a Cluttered Environment using Differential Evolution', in 2020 IEEE Symposium Series on Computational Intelligence (SSCI 2020), IEEE, Due to COVID-19 restrictions, the event was held virtually with the broadcast from Canberra, Australia., pp. 2194 - 2201, presented at 2020 IEEE Symposium Series on Computational Intelligence (SSCI), Due to COVID-19 restrictions, the event was held virtually with the broadcast from Canberra, Australia., 01 December 2020 - 04 December 2020, http://dx.doi.org/10.1109/SSCI47803.2020.9308572
    Conference Papers | 2020
    Elsayed S; Singh H; Debie E; Perry A; Campbell B; Hunjet R; Abbass H, 2020, 'Path Planning for Shepherding a Swarm in a Cluttered Environment using Differential Evolution', http://dx.doi.org/10.48550/arxiv.2008.12639
    Conference Papers | 2020
    Moustafa N; Hassan M; Debie E; Janicke H, 2020, 'Federated TON_IoT Windows Datasets for Evaluating AI-based Security Applications', Guangzhou, China, presented at The 19th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, Guangzhou, China, 31 December 2020
    Preprints | 2020
    Moustafa N; Keshk M; Debie E; Janicke H, 2020, Federated TON_IoT Windows Datasets for Evaluating AI-based Security Applications, , http://dx.doi.org/10.48550/arxiv.2010.08522
    Conference Papers | 2019
    Fernandez Rojas R; Debie E; Fidock J; Barlow M; Kasmarik K; Anavatti S; Abbass H; Garratt M, 2019, 'Encephalographic Assessment of Situation Awareness in Teleoperation of Human-Swarm Teaming', in Neural information processing : 26th International Conference, ICONIP 2019, Sydney, NSW, Australia, December 12-15, 2019, Proceedings. Part IV, Sydney, presented at International Conference on Neural Information Processing, Sydney, 12 December 2019, http://dx.doi.org/10.1007/978-3-030-36808-1_58
    Conference Papers | 2018
    Nguyen T; Nguyen H; Debie E; Kasmarik K; Garratt M; Abbass H, 2018, 'Swarm Q-Learning With Knowledge Sharing Within Environments for Formation Control', Brazil, presented at International Joint Conference on Neural Networks, Brazil, -
    Conference Papers | 2016
    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
    Conference Papers | 2014
    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
    Conference Papers | 2013
    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.), 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
    Conference Papers | 2013
    Debie E; Shafi K; Lokan CJ, 2013, 'REUCS-CRG: Reduct based Ensemble of sUpervised Classifier System with Combinatorial Rule Generation for Data Mining', in Blum, Christian (ed.), Amsterdam, pp. 1251 - 1258, presented at 2013 Genetic and Evolutionary Computation Conference, Amsterdam, 06 July 2013 - 10 July 2013, http://dx.doi.org/10.1145/2464576.2482703
    Conference Papers | 2013
    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
    Conference Papers | 2012
    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