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أ.د.هيا محمد عبدالعزيز العسكر

أستاذ قسم علوم الحاسب كلية هندسة وعلوم الحاسب بالخرج
  • الخرج
  • 011-588-8810
  • h.alaskar@psau.edu.sa
  • السيرة الذاتية
  • الأبحاث العلمية

المؤهلات العلمية

  • 2003–2006. Bachelor of Computer science with honor. Girls College, Ministry of Education, Saudi Arabia. • 2008–2009. M. Sc in applied artificial intelligence. Dissertation: Investigation into Spectral Clustering University of Exeter, UK • 2011–2014. PhD in Computer science. Dissertation: Dynamic Self Organized Neural Network Inspired by the Immune Algorithm for Financial Time Series Prediction and Medical Data . Liverpool John Moores University, UK

الخبرات

  • 2018 - حتى الآن - وكيله كليه هندسه وعلوم الحاسب - كلية هندسة وعلوم الحاسب

مهام ومسؤوليات

  • 2014 Assistant Professor at College of Engineering and Computer Sciences, Prince Sattam University, AlKharj, SA. 2015 Vice Dean for Academic administrative. 2015 The head of Computer Science department. 2015 Member of strategic objective committee for Building an Effective Local and Global Partnership. 2015 Vice Dean of College of Engineering and Computer Sciences (Female Section) Prince Sattam University 2017: Faculty member and Assistant of Quality and Accreditation responsible at College of Engineering and Computer Sciences (Female Section) Prince Sattam University. 2017: Member of the Higher Committee for Academic Affairs at College of Engineering and Computer Sciences (Female Section) Prince Sattam University. 2017: Member of higher education Committee at College of Engineering and Computer Sciences (Female Section) Prince Sattam University. 2018: Member of Curriculum Development Committee at College of Engineering and Computer Sciences (Female Section) Prince Sattam University. 2018: Member of graduate student committees at College of Engineering and Computer Sciences (Female Section) Prince Sattam University. 2018: Vice Dean of College of Engineering and Computer Sciences (Female Section) Prince Sattam University. 2018: Member of the Strategic Planning Committee at the college of Engineering and Computer Sciences Prince Sattam University. 2018: Member of scientific research Committee at College of Engineering and Computer Sciences (Female Section) Prince Sattam University. 2019: Member of Disciplinary Committee, Prince Sattam University. 2019: Member of Community Service Committee at College of Engineering and Computer Sciences (Female Section) Prince Sattam University
  • • Academic leader workshop, 2020 • Women in Data Science Forum, Prince Sultan University, 2019 • Workplace dialogue training workshop, organized by dialogue Academy for training, 2019. • Common Mistakes in data science, organized by IoT conference, 2019. • How to Evaluate Scientific Production workshop, organized by PSAU, 2018. • Women leadership in Higher Education workshop, organized by Academic Leadership Center. 2018 • Achieving Excellence in Graduate Education workshop, organized by Academic Leadership Center. 2018 • Decision making and problem solving, organized by Academic Leadership Center. 2018 • Robot-Proof: Higher Education in the Age of Artificial Intelligence, organized by Academic Leadership Center. 2018. • The requirements of developed Quality Assurance and Accreditation of Higher Education programs, organized by NCAAA, 2018. • The requirements of Quality Assurance and Accreditation of Higher Education Institutions, organized by NCAAA, 2018. • The Standards of Quality Assurance and Accreditation of Higher Education Programs, organized by NCAAA, 2018. • "PSAU-Board of Assessors" training program organized by PSAU, 2018. • Social Media Data Analytics, online course From Coursera. 2017. • IBM Blockchain Foundation for Developers, online course From Coursera, 2018 • Blackboard workshop, From PSAU, 2016. • Cloud infrastructure and services v2 " From EMC, 2015. • Smart board workshop, From PSAU, 2015. • Managing Stress and Pressure at Work, From PSAU, 2015

الأبحاث العلمية

  • H Alaskar, AJ Hussain, W Khan, H Tawfik, P Trevorrow, P Liatsis, Z Sbaï (2020) data
  • science approach for reliable classification of neuro-degenerative diseases using gait ,
  • Journal of Reliable Intelligent Environments, 1-15
  • Khan, A Hussain, K Kuru, H Al-Askar, (2020)Pupil Localisation and Eye Centre
  • Estimation Using Machine Learning and Computer Vision, Sensor
  • Ahmed, Z., Hussain, A., Khan, W., Baker, T., Al-Askar, H., Lunn, J., Liatsis, P., Al-Jumeily,
  • D., Al-Shabandar, R., (2020). Lossy and Lossless Video Frame Compression: A Novel
  • Approach for the High-Temporal Video Data Analytics. Remote Sensing, ISI, Scopus.
  • M IoT-Enabled Flood Severity Prediction via Ensemble Machine Learning Models
  • Khalaf, H Alaskar, AJ Hussain, T Baker, Z Maamar, R Buyya, P Liatsis,IEEE Access 8,
  • 70375-70386
  • A Abdullahi, K Bawazeer, S Alotaibai, E Almoaither, M Al-Otaibi, H, alaskar,Pretrained
  • Convolutional Neural Networks for Cancer Genome Classification,3rd International
  • Conference on Computer Applications & Information
  • A Robust Quasi-Quantum Walks-Based Steganography Protocol for Secure Transmission
  • of Images on Cloud-Based E-healthcare Platforms
  • B Abd-El-Atty, AM Iliyasu, H Alaskar, A El-Latif, A Ahmed
  • Sensors 20 (11), 3108.
  • W Khan, A Hussain, H Alaskar, T Baker, F Ghali, D Al-Jumeily, 2020, Prediction of
  • Flood Severity Level Via Processing IoT Sensor Data Using Data Science Approach,
  • IEEE Internet of Things Magazine
  • H Alaskar, T Vaiyapuri, Z Sbai, 2019, Twitter Analytics for Discovering Socially
  • Important Locations for Business Improvement, IEEE International Symposium on Signal
  • Processing and Information …
  • Alaskar, H., (2019). High Predictive Performance of Dynamic Neural Network Models
  • for Forecasting Financial Time Series, ISI, Scopus.
  • Alaskar H., Alzhrani N., Hussain A., Almarshed F. (2019) The Implementation of
  • Pretrained AlexNet on PCG Classification. In: Huang DS., Huang ZK., Hussain A. (eds)
  • Intelligent Computing Methodologies. ICIC 2019. Lecture Notes in Computer Science,
  • vol 11645. Springer, Cham. ISI, Scopus.
  • Haya Alaskar, A. Hussain, Nourah Alaseem, Panos Liatsis, Dhiya Al-Jumeily:
  • Application of Convolutional Neural Networks for Automated Ulcer Detection in
  • Wireless Capsule Endoscopy Images. Sensors 19(6): 1265 (2019). ISI, Scopus. IF: 3.031.
  • H.Alaskar, 2018 Deep Learning-Based Model Architecture for Time-Frequency Images
  • Analysis, International Journal of Advanced Computer Science and Applications. ISI,
  • Scopus.
  • H. Alaskar, 2018, Deep Learning of EMG Time Frequency Representations for
  • Identifying Normal and Aggressive Actions, International Journal of Computer Science
  • and Network Security, Vol. 18 No. 12 pp. 16-25,
  • http://paper.ijcsns.org/07_book/201812/20181203.pdf. ISI
  • H. Alaskar, A. Hussain, 2018 ,Prediction of Parkinson Disease Using Gait Signals,
  • Eleventh International Conference on Developments in e-Systems Engineering, IEEE.ISI
  • Haya Alaskar , Convolutional Neural Network Application in Biomedical Signals, Journal
  • of Computer Science and Information Technology, American Research Institute, 2018,
  • Vol. 6, No. 2, pp. 45-59.
  • H. Tawfik, H. Alaskar, P. Liatsis, M. khalaf , 2018:A Dynamic Neural Network
  • Architecture with immunology Inspired Optimization for
  • Weather Data Forecasting , Big Data Research. ISSN 2214-5796 . ISI, Scopus.
  • IF:2.952
  • H. Alaskar, A. Hussain, Data Mining to Support the Discrimination of Amyo-trophic
  • lateral sclerosis Diseases Based on Gait Analysis In: Huang DS., Gromiha M., Han K.,
  • Hussain A. (eds) Intelligent Computing Methodologies. ICIC 2018. Lecture Notes in
  • Computer Science, vol 10956. Online ISBN 978-3-319-95957-3, DOI
  • https://doi.org/10.1007/978-3-319-95957-3_80, ISI, Scopus.
  • H. Alasker , S. Alharkan, W. Alharkan ; A. Zaki ; L. Septem Riza,
  • 2017,Detection of kidney disease using various intelligent classifiers, Science in
  • Information Technology (ICSITech), 2017 3rd International Conference . IEEE
  • explore.
  • H. Alasker , A. Zaki , 2017Early Prediction of Chronic Kidney Disease Using Multiple
  • Automated Techniques, International Journal of Computing & Information Sciences
  • M. Khalaf, D. Al-Jumeily, R. Keight, R. Keenan, P. Fergus, H. Al-Askar, A. Shaw, I.
  • Idowu :Training Neural Networks as Experimental Models: Classifying Biomedical
  • Datasets for Sickle Cell, In: Huang DS., Bevilacqua V., Premaratne P. (eds) Intelligent
  • Computing Theories and Application. ICIC 2016. Lecture Notes in Computer Science,
  • vol 9771. Springer, Cham, Online ISBN 978-3-319-42291-6. DOI
  • https://doi.org/10.1007/978-3-319-42291-6_78 , ISI, Scopus. IF : 0.402
  • C. Montañez, P. Fergus, D. Al-Jumeily, B. Abdulaimma, H. Al-Askar :A Genetic
  • Analytics Approach for Risk Variant Identification to Support Intervention Strategies for
  • People Susceptible to Polygenic Obesity and Overweight. In: Huang DS., Bevilacqua V.,
  • Premaratne P. (eds) Intelligent Computing Theories and Application. ICIC 2016. Lecture
  • Notes in Computer Science, vol 9771. Springer, Cham, Online ISBN 978-3-319-42291-6 ,
  • DOI https://doi.org/10.1007/978-3-319-42291-6_80, ISI, Scopus.IF : 0.402
  • Al Kafri, S. Sudirman, P. Fergus, D. Al-Jumeily, M. Al-Jumaily, H. Al-Askar, A
  • Framework on a Computer Assisted and Systematic Methodology for Detection of
  • Chronic Lower Back Pain Using Artificial Intelligence and Computer Graphics
  • Technologies. . ICIC 2016. Lecture Notes in Computer Science, Springer, Cham. ISI,
  • Scopus. IF : 0.402
  • A.Hussain, D.Al-Jumeily, H. Al-Askar, N. Radi:
  • Regularized dynamic self-organized neural network inspired by the immune
  • algorithm for financial time series prediction. Neurocomputing 188: 23-30 (2016).
  • ISI, Scopus. IF: 3.317.
  • H. Alaskar, D. J. Lamb, A. Hussain, D. Al-Jumeily, M. Randles, P. Fergus:
  • Predicting financial time series data using artificial immune system-inspired neural
  • networks. IJAISC 5(1): 45-68 (2015)
  • A. Hussain, P. Fergus, H. Al-Askar, D. Al-Jumeily, F. Jager:
  • Dynamic neural network architecture inspired by the immune algorithm to predict
  • preterm deliveries in pregnant women. Neurocomputing 151: 963-974 (2015). ISI,
  • Scopus. IF: 3.317.
  • Reid D., Tawfik H., Hussain A.J., Al-Askar H. (2015) Forecasting Weather Signals Using
  • a Polychronous Spiking Neural Network. In: Huang DS., Bevilacqua V., Premaratne P.
  • (eds) Intelligent Computing Theories and Methodologies. ICIC 2015. Lecture Notes in
  • Computer Science, vol 9225. Springer, Cham
  • A. Hussain, P. Fergus, D. Al-Jumeily, H. Alaskar, N. Radi:
  • The Utilisation of Dynamic Neural Networks for Medical Data Classifications- Survey
  • with Case Study. ICIC (3) 2015: 752-758
  • A. Hussain, D. Al-Jumeily, H. Al-Askar “The Application of Dynamic Self-organised
  • Multilayer network Inspired by the Immune Algorithm for weather signals forecast”, The
  • Third International Conference on Technological Advances in Electrical, Electronics and
  • Computer Engineering, TAEECE 2015, Beirut, Lebanon, 2015.
  • I. Idowu, Paul Fergus, A. Hussain, Chelsea Dobbins, H. Al-Askar:
  • Advance Artificial Neural Network Classification Techniques Using EHG for Detecting
  • Preterm Births. CISIS 2014, IEEE explore, 95-100
  • Hussain A.J., Al-Askar H., Al-Jumeily D. (2014) Physical Time Series Prediction Using
  • Dynamic Neural Network Inspired by the Immune Algorithm. In: Bouchachia A. (eds)
  • Adaptive and Intelligent Systems. ICAIS 2014. Lecture Notes in Computer Science, vol
  • 8779. Springer, Cham
  • Al-Askar H., Hussain A.J., Al-Jumeily D., Radi N. (2014) Regularized Dynamic Self
  • Organized Neural Network Inspired by the Immune Algorithm for Financial Time Series
  • Prediction. In: Huang DS., Han K., Gromiha M. (eds) Intelligent Computing in
  • Bioinformatics. ICIC 2014. Lecture Notes in Computer Science, vol 8590. Springer,
  • Cham
  • Alaskar H., Hussain A.J., Paul F.H., Al-Jumeily D., Tawfik H., Hamdan H. (2014)
  • Feature Analysis of Uterine Electrohystography Signal Using Dynamic Self-organised
  • Multilayer Network Inspired by the Immune Algorithm. In: Huang DS., Bevilacqua V.,
  • Premaratne P. (eds) Intelligent Computing Theory. ICIC 2014. Lecture Notes in
  • Computer Science, vol 8588. Springer, Cha
  • Evaluation of Advanced Artificial Neural Network Classification and Feature Extraction
  • Techniques for Detecting Preterm Births Using EHG Records. In: Huang DS., Han K.,
  • Gromiha M. (eds) Intelligent Computing in Bioinformatics. ICIC 2014. Lecture Notes in
  • Computer Science, vol 8590. Springer, Cham
  • Huang R., Tawfik H., Hussain A.J., Al-Askar H. (2014) The Application of Artificial
  • Immune Systems for the Prediction of Premature Delivery. In: Huang DS., Jo KH., Wang
  • L. (eds) Intelligent Computing Methodologies. ICIC 2014. Lecture Notes in Computer
  • Science, vol 8589. Springer, Cham
  • D. Al-Jumeily ; A. Hussain ; H. Alaskar (2013) Recurrent neural networks inspired by
  • artificial Immune algorithm for time series prediction. The 2013 International Joint
  • Conference on Neural Networks (IJCNN) Dallas, TX, USA: 1-8.
  • Invited Book Chapters:
  • “Recurrent Neural Networks in Medical Data Analysis and Classifications”,
  • in: D. Al-Jumeily, A. Hussain, C. Mallucci, C. Oliver (eds), Applied Computing
  • in Medicine and Health, Elsevier, 2015.

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إدارة العلاقات العامة والإعلام

  • للاتصال من داخل الجامعة 1200
  • للاتصال من خارج الجامعة 011-588-1200
  • البريد الإلكترونى pr@psau.edu.sa
  • لطلب خدمة وفتح بلاغ للأعطال ithelp.psau.edu.sa

© جامعة الأمير سطام بن عبد العزيز 2022

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