Associate Professor of Information Technology
Dr. Khaled Alomari is a seasoned Associate Professor of IT at Abu Dhabi University, with a robust background spanning various facets of Information Technology. His experience ranges from roles as an Instructor of IT, Senior Instructor, Assistant Professor, and an Academic Coordinator at Abu Dhabi University to a Computer Teacher and Trainer in Jordan. Dr. Alomari’s academic qualifications are equally impressive, including a Ph.D. in Computer Science and a Master of Business Administration. He has made significant contributions to the field with numerous publications, showcasing his in-depth research and knowledge. Dr. Alomari’s extensive training certifications and courses reflect his commitment to continuous learning and expertise in areas like Microsoft technologies, instructional design, and remote work foundations. His diverse teaching portfolio covers subjects from computer skills and data analysis to entrepreneurship and management information systems, underscoring his multifaceted proficiency in the realm of IT and education.
2023 — Present
2020 : 2022
2012 : 2015
2014 : 2017 – British University in Dubai (BUID)
2018 : 2021 – Abu Dhabi University
2006 : 2009 – Arab Academy for Banking and Financial Sciences (AABFS)
2001 : 2005 – Jerash Private University
Mbaidin, H. O., Alomari, K. M., AlMubydeen, I. O., & Sbaee, N. Q. (2024). The critical success factors (CSF) of blockchain technology effecting excel performance of banking sector: Case of UAE Islamic Banks. International Journal of Data and Network Science, 8(1), 289–306. https://doi.org/10.5267/j.ijdns.2023.9.024
AlHamad, A. Q., Alomari, K. M., Alshurideh, M., Al Kurdi, B., Salloum, S., & Al-Hamad, A. Q. (2022). The Adoption of Metaverse Systems: A hybrid SEM – ML Method. In 2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) (pp. 1–5). IEEE. https://doi.org/10.1109/ICECCME55909.2022.9988215
AlLouzi, A. S., & Alomari, K. M. (2023). Adequate legal rules in settling metaverse disputes: Hybrid legal framework for metaverse dispute resolution (HLFMDR). International Journal of Data and Network Science, 7(4), 1627–1642. https://doi.org/10.5267/j.ijdns.2023.8.001
Alomari, K. M. (2022). Predicting the intention to use social media among medical students in the United Arab Emirates: A machine learning approach. South Eastern European Journal of Public Health (SEEJPH)), 5. https://doi.org/10.11576/seejph-5827
Alomari, K. M., ElSherif, H. M., & Shaalan, K [Khaled]. (2017). Arabic Tweets Sentimental Analysis Using Machine Learning. In S. Benferhat, K. Tabia, & M. Ali (Eds.), Lecture Notes in Computer Science: Vol. 10350. Advances in Artificial Intelligence: From Theory to Practice (Vol. 10350, pp. 602–610). Springer International Publishing. https://doi.org/10.1007/978-3-319-60042-0_66
Alomari, K. M., Mbaidin, H. O., Al Jbour, R. S., & ALLAHAWIAH, S. R. (2022). THE IMPACT OF QUALITY MOBILE E-GOVERNEMENT SERVICIS ON SERVICE USAGE : THE MEDIATING ROLE CITIZEN’S SATISFACTION. Journal of Theoretical and Applied Information Technology, 100(24). http://www.jatit.org/volumes/Vol100No24/3Vol100No24.pdf
Alomari, K. M., Ncube, C., & Shaalan, K [Khaled]. (2018). Predicting Success of a Mobile Game: A Proposed Data Analytics-Based Prediction Model. In M. Mouhoub, S. Sadaoui, O. Ait Mohamed, & M. Ali (Eds.), Lecture Notes in Computer Science: Vol. 10868. Recent Trends and Future Technology in Applied Intelligence (Vol. 10868, pp. 127–134). Springer International Publishing. https://doi.org/10.1007/978-3-319-92058-0_12
Alomari, K. M., Soomro, T. R., & Shaalan, K [Khaled]. (2016). Mobile Gaming Trends and Revenue Models. In H. Fujita, M. Ali, A. Selamat, J. Sasaki, & M. Kurematsu (Eds.), Lecture Notes in Computer Science: Vol. 9799. Trends in Applied Knowledge-Based Systems and Data Science (Vol. 9799, pp. 671–683). Springer International Publishing. https://doi.org/10.1007/978-3-319-42007-3_58
Alomari,, K. M., AlHamad, Q. A., Mbaidin, H. O., & Salloum, S. (2019). Prediction of the Digital Game Rating Systems based on the ESRB. Opción, 35(19), 1368–1393. https://produccioncientificaluz.org/index.php/opcion/article/view/24085
Elsherif, H. M., Alomari, K. M., Alhaddad, A., & Alkatheeri, A. O. (2016). Mobile government services satisfaction and usage analysis: UAE government smart services case study. International Journal of Computer Science and Mobile Computing, 5(3), 291–302. Find Here
Elsherif, H. M., Alomari, K. M., Alhamad, A. Q., & Shaalan, K [K.]. (2019). Arabic Rule-based Named Entity Recognition System Using GATE. In P. Perner (Ed.), 15th International Conference on Machine Learning and Data Mining, MLDM 2019. Click here
Maghaydah, S., Maheshwari, P., & Alomari, K. M. (2023). Agent-Based Modelling and Simulation of Crowd Evacuation: Case Study for Electric Train Cabin. In 2023 International Conference on Business Analytics for Technology and Security (ICBATS) (pp. 1–7). IEEE. https://doi.org/10.1109/ICBATS57792.2023.10111239
Mbaidin, H. O., Alomari, K. M., & Al Jbour, R. S. (2021). The Impact of E-Services Quality on Citizens Satisfaction: An Applied Study at Al Ain Municipality UAE. International Journal of Entrepreneurship, 25(5S), 1–13. Find here
Mobideen, H., Allahawiah, S., & Alomari, K. M. (2019). The Impact of Human Resources Information Systems on Human Resources Selection and Recruitment Strategy: An applied study on Arab Potash Company in the Hashemite Kingdom of Jordan. International Journal of Advanced Trends in Computer Science and Engineering, 8(5), 2475–2484. https://doi.org/10.30534/ijatcse/2019/93852019