Artificial Intelligence & Data Science

The Artificial Intelligence Research Group is a noteworthy scientific and technology research group that tackles unsolved challenges and pushes the boundaries of research. Its goal is to create a natural environment that will support the artificial intelligence industry and its technological development, as well as investigating major biomedical applications, smart city applications, and intelligent decision-making systems. The ultimate outcome of this group is enhancing the region's leading position and the overall scientific research strength. The first round of articles will concentrate on fundamental research including the use of deep learning and evolutionary intelligence to cancer diagnostics and disease detection in particular. Genetic data compression and recognition, medical image recognition and diagnosis, medical knowledge mapping and natural language processing, and finally intelligent health care application platforms are the four main areas of the research. Furthermore, the group focuses on the use of deep neural networks for bioinformatics and data science applications, the use of artificial intelligence and the Internet of Medical Things for medical devices, fusion-based feature extraction from medical images, and finally, proposing an AI-enabled framework for healthcare big data.

Research Plan 2021-2022

3

Active UBT Researchers

9

International Researchers

7

Articles in Q1/Q2 journals

Active UBT Researchers

Dr Bassam A. Y. Alqaralleh

Dr Bassam A. Y. Alqaralleh, PhD, MSc, BSc in Computer Science, graduate Dip. in Computer Information Systems, UTS University and University of Sydney – Australia. Research interests include Distributed Systems, Artificial Intelligence, Smart Applications, Wireless Networking, Load-Balancing in P2P systems, mobile banking, mobile government, Technology adoption and acceptance and Security Systems.
Dr. Bassam Alqaralleh - Google ScholarDr. Bassam Alqaralleh - Google Scholar
Bassam Alqaralleh (0000-0003-2232-9387) (orcid.org)

Raed Ahmed Alawfi

Raed Ahmed Alawfi, MSc in Machine Learning and Artificial intelligence, University of Wisconsin-Milwaukee. Head of Software Engineering Department. Research interests: Machine learning and AI applications such as Deep learning, Computer Vision and Natural Language Processing.

Dr. Halah Nassif

Dr. Halah Nassif, PhD in E-Research and Technology Enhanced Learning, Lancaster University, UK. Lecturer in MIS. Research interests: Technology enhanced learning, e-learning utilization, learning analytics, educational data mining, AI, and Saudi Arabia higher education.

International Collaborating Researchers

Dr Anas Abu Karaki

Dr Anas Abu Karaki, Ph.D, Dorman University, Sudan, MSc., UWS, Australia, BSc. in Computer Science, ISRAA University, Jordan. Assistant Professor, Al-Hussein Bin Talal University (AHU), Jordan. Research interests: Sensor Networks, Decision Support System, Machine Learning, Knowledge Managements, and Mobile Learning.

Dr K. Shankar

Dr K. Shankar, PhD Computer Science, Alagappa University, Karaikudi, India. Senior Member, IEEE, and Postdoctoral Fellow with the Federal University of Piauí, Brazil. Authored/co-authored 108 ISI Journal articles, 100 Scopus Indexed Articles. Besides, and authored/edited 6 international books. Research interests: Healthcare applications, Secret Image Sharing Scheme, Digital Image Security, Cryptography, Internet of Things, and Optimization algorithms.

Dr Esam Alqaralleh

Dr Esam Alqaralleh, Ph.D. electrical engineering, National Chiao Tung University, Taiwan. Dean of the King Abdullah II School of Engineering, and Senior Member of IEEE. Research interests: Video coding/motion estimation, Machine learning and AI application, Embedded Systems/RTOS, Engineering Education, and Arabic Handwritten Recognition.

Dr Ahmed Alomari

Dr Ahmed Alomari, Ph.D., M.Sc., B. Sc. Computer Science. Dean, Faculty of Information Technology FIT, Applied Science University, Amman-Jordan. Research interests: MANET, Encryption, RTA, and e-government.

Dr. Deepak Gupta

Dr. Deepak Gupta, Ph.D., AKTU University, India M.Eng., Delhi Technological University, India, B.Tech., Guru Gobind Singh Indraprastha University, India. Research interests: Intelligent Data Analysis, Nature-Inspired Computing, Machine Learning and Soft Computing.

Dr. Irina V. Pustokhina

Dr. Irina V. Pustokhina, Ph.D., MBA, logistics and supply chain management, State University of Management, Russia. Associate Professor, Plekhanov Russian University of Economics, Moscow. Research interests: Supply chain management, regional logistics development, sustainable urban development, city logistics, intelligent logistics systems, big data technology and applications, information management, and the Internet of Things.

Dr. Gyanendra Prasad Joshi

Dr. Gyanendra Prasad Joshi, Ph.D., M.Sc. information and communication engineering, Yeungnam University, South Korea. Assistant Professor, Sejong University, South Korea. Research interests: UAV localization, MAC and routing protocols for next generation wireless networks, wireless sensor networks, cognitive radio networks, RFID systems, the IoT, smart city, deep learning, block chain, and digital convergence.

Dr. Seifedine Kadry

Dr. Seifedine Kadry, Ph.D., Blaise Pascal University, France, M.S., Reims University, France, and EPFL, Lausanne, B.Sc., Lebanese University. Senior Member, IEEE. Research interests: Data science, education using technology, system prognostics, stochastic systems, and applied mathematics.

Current Research Projects

  • Design of Fusion based Tongue Color Image Analysis Model for Biomedical Applications
  • Optimal deep learning-based Inception model for cervical cancer diagnosis using Pap smear images
  • Deep Neural Networks for Bioinformatics and Data Science Applications
  • AI based Intelligent Decision-Making System for Financial Crisis Prediction
  • Explainable AI and Internet of Medical Things for medical devices
  • Deep Learning and Evolutionary Intelligence with Fusion-based Feature Extraction from Medical Images
  • A novel AI-enabled framework for healthcare big data
  • Automatic Vehicle License Plate Recognition Using Optimal Deep Learning Model for Smart Cities

Research Publications

  • Al Qaralleh, E. A., Nassif, H., & Alqaralleh, B. A. (2022). Fusion Based Tongue Color Image Analysis Model for Biomedical Applications. CMC-COMPUTERS MATERIALS & CONTINUA, 71(3), 5477-5490.
  • AbuKhalil, T., Alqaralleh, B. A., & Al-Omari, A. H. Optimal Deep Learning Based Inception Model for Cervical Cancer Diagnosis.
  • Qaralleh, Esam & Aldhaban, Fahad & Nasseif, Halah & Alqaralleh, Bassam & Abukhalil, Tamer. (2022). Hybrid Metaheuristics Based License Plate Character Recognition in Smart City. Computers, Materials & Continua. 72. 5727-5740. 10.32604/cmc.2022.026780.
  • Qaralleh, Esam & Aldhaban, Fahad & Nasseif, Halah & Alksasbeh, Malek & Alqaralleh, Bassam. (2022). Smart Deep Learning Based Human Behaviour Classification for Video Surveillance. Computers, Materials and Continua. 72. 5593- 5605. 10.32604/cmc.2022.026666.
  • Feras Mohammed A-Matarneh, Bassam A. Y. Alqaralleh, Fahad Aldhaban, Esam A. AlQaralleh, Anil Kumar, Deepak Gupta, Gyanendra Prasad Joshi, "Swarm Intelligence with Adaptive Neuro-Fuzzy Inference System-Based Routing Protocol for Clustered Wireless Sensor Networks", Computational Intelligence and Neuroscience, vol. 2022, Article ID 7940895, 11 pages, 2022. https://doi.org/10.1155/2022/7940895
  • Feras Mohammed A-Matarneh, Bassam A. Y. Alqaralleh, Fahad Aldhaban, Esam A. AlQaralleh, Anil Kumar, Deepak Gupta, Gyanendra Prasad Joshi, "Swarm Intelligence with Adaptive Neuro-Fuzzy Inference System-Based Routing Protocol for Clustered Wireless Sensor Networks", Computational Intelligence and Neuroscience, vol. 2022, Article ID 7940895, 11 pages, 2022. https://doi.org/10.1155/2022/794089
  • Alqaralleh, B. A., Aldhaban, F., A-Matarneh, Feras Mohammed, & AlQaralleh, E. A. (2022). Automated Handwriting Recognition and Speech Synthesizer for Indigenous Language Processing. CMC-COMPUTERS MATERIALS & CONTINUA, 72(2), 3913- 3927.
  • B. A. Y. Alqaralleh, F. Aldhaban, E. A. AlQarallehs and A. H. Al-Omari, "Optimal machine learning enabled intrusion detection in cyber-physical system environment," Computers, Materials & Continua, vol. 72, no.3, pp. 4691–4707, 2022.
  • Alqaralleh, Bassam & Aldhaban, Fahad & Abukaraki, Anas & Qaralleh, Esam. (2022). Evolutionary Intelligence and Deep Learning Enabled Diabetic Retinopathy Classification Model. Computers, Materials & Continua. 73. 87-101. 10.32604/cmc.2022.026729.

Other Related Groups

Management
Science & Engineering
Economics & Finance