Mamoun Mardini, Ph.D.

Published: August 23rd, 2018

Category: Uncategorized

Profile Picture


Assistant Professor


2004 Mowry Road, Gainesville, Fl 32611
PO Box 100107, Gainesville, FL 32610.






Departmental Affiliation

Department of Aging and Geriatric Research, Data Science and Applied Technology Core


2018 Ph.D., Computer Science, University of North Carolina, Charlotte, USA
2013 M.S., Computer Engineering, American University of Sharjah, UAE
2009 B.S., Computer Engineering, Jordan University of Science and Technology, Jordan

Additional Information

Mamoun Al-Mardini is an Assistant Professor in the Department of Aging and Geriatric Research, Division of Clinical Research at the University of Florida. He finished his Ph.D. in Computer Science from the University of North Carolina-Charlotte in 2018. His research interests lie in the broad area of data science with an emphasis on Healthcare Analytics. His primary research concerns analyzing big data and extracting insightful knowledge. Additionally, he is interested in the area of Internet of Things (IoT) and its applications in healthcare, such as remote healthcare monitoring systems for elderly, mobile-Health, and autonomous vehicles.

Professional Interests

Data Science
Health Analytics
Internet of Things (IoT)
Remote Healthcare Monitoring
Autonomous Vehicles

Curriculum Vitae



Google Scholar

  1. Mardini M, Raś ZW. Extraction of Actionable Knowledge to Reduce Hospital Readmissions through Patients Personalization. Information Sciences.485(1): 1-17, 2019
  2. Mardini M, Iraqi Y, Agoulmine N. A Survey of Healthcare Monitoring Systems for Chronically Ill Patients and Elderly. Journal of Medical Systems. 43(3): 50, 2019
  3. Almardini, M., Raś,W., “A Supervised Model for Predicting the risk of Mortality and Hospital Readmissions for Newly Admitted Patients,” Foundations of Intelligent Systems, Proceedings of ISMIS’17 in Warsaw, Poland, LNAI, Vol. 10352, Springer, 2017, 29-36
  4. Almardini, M., Hajja, A., Raś, Z.W., Clover, L., Olaleye, D., “Predicting the primary medical procedure through clustering of patients’ diagnoses,” New Frontiers in Mining Complex Patterns, Post-proceedings of NFMCP 2016, ECML/PKDD Workshop in Riva del Garda, Italy, LNAI, Vol. 10312, Springer, 2017, 117-131
  5. Almardini, M., Hajja, A., Clover, L., Olaleye, D., Park, Y., Paulson, J., Xiao, Y., “Reduction of Hospital Readmissions Through Clustering Based Actionable Knowledge Mining,” Proceedings of IEEE/WIC/ACM International Conference on Web Intelligence (WI’16), IEEE Computer Society, 2016.
  6. Almardini, M., Hajja, A., Raś, Z.W., Clover, L., Olaleye, D., Park, Y., Paulson, J., Xiao, Y., “Reduction of Readmissions to Hospitals Based on Actionable Knowledge Discovery and Personalization,” in Beyond Databases Architectures and Structures – BDAS, Conference Proceedings, (Eds. D. Mrozek, et al.), Communications in Computer and Information Science, Vol. 613, Springer, 2016, 39-55
  7. Al-Mardini, M., Aloul, F., Sagahyroon, A., & Al-Husseini, L., “Classifying Obstructive Sleep Apnea using Smartphones,” Journal of biomedical informatics, Elsevier, vol. 52, pp. 251-259, 2014.
  8. Al-Mardini, M., Aloul, F., Sagahyroon, A., & Al-Husseini, L., “On the use of smartphones for detecting obstructive sleep apnea,” IEEE 13th International Conference on Bioinformatics and Bioengineering (BIBE), pp. 1-4. 2013.
  9. Al-Mardini, M., Aloul, F., Sagahyroon. A., “A Framework for Screening and Classifying Obstructive Sleep Apnea Using Smartphones,” Dissertation, American University of Sharjah: DSpace, July 2013.
  10. Al-Ali, A., Qasaimeh, M., Al-Mardini, M., Radder, S., & Zualkernan, I., “ZigBee-Based Irrigation System for Home Gardens,” IEEE International Conference on Communications, Signal Processing, and their Applications (ICCSPA’15), pp. 1-5, 2015.
  11. Aloul, F., Al-Ali, A., Al-Dalky, R., Al-Mardini, M., & El-Hajj, W., “Smart Grid Security: Threats, Vulnerabilities and Solutions,” International Journal of Smart Grid and Clean Energy (IJSGCE), vol. 1, no. 1, 2012.