Assistant Professor

2022, PhD in Computer Science, Western Sydney University
2017, Master of Science in Computing, Western Sydney University


Dr. Belal Alsinglawi holds a PhD in Computer Science from Western Sydney University. He completed his Master of Science in Computing from the same university. He is currently an Assistant Professor at CIS, Zayed University, UAE. He boasts an extensive and diverse career in STEM, both in academia and industry, where he has played a central role and led various research, IT industrial projects, and research and development (R&D) initiatives in Australia and internationally. He has worked and collaborated with key industrial stakeholders, government agencies, corporations, and non-profit organizations on multiple research projects and industrial R&D fellowships at Australian universities, focusing on the Internet of Things, Artificial Intelligence, and Cybersecurity. His work involves applying cutting-edge techniques and transferring research outcomes to solve real-world problems. His extensive professional experience in IT also includes roles as an IT systems engineer and consultant for various organizations, as well as involvement in digital health and data analytics projects.


Abu Dhabi - Khalifa City, MF!-1-043


+971 2 599 3892

Teaching Areas

Artificial Intelligence
Internet of Things

Research and Professional Activities

Alsinglawi, B. and Wickramasinghe, N., 2024. Privacy-Preserving Roadmap for Medical Data-Sharing Systems. In Dimensions of Intelligent Analytics for Smart Digital Health Solutions (pp. 121-152). Chapman and Hall/CRC.

Neupane, I., Alsinglawi, B. and Rabie, K., 2023, March. Indoor Positioning using Wi-Fi and Machine Learning for Industry 5.0. In 2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) (pp. 359-362). IEEE.

Alsinglawi, B. and Rabie, K., 2023, March. eDeepRFID-IPS: Enhanced RFID Indoor Positioning with Deep Learning for Internet of Things. In International Conference on Advanced Information Networking and Applications (pp. 149-158). Cham: Springer International Publishing.

Alsinglawi, B., Alshari, O., Alorjani, M., Mubin, O., Alnajjar, F., Novoa, M. and Darwish, O., 2022. An explainable machine learning framework for lung cancer hospital length of stay prediction. Scientific reports, 12(1), p.607.

Elkhodr, M. and Alsinglawi, B., 2020. Data provenance and trust establishment in the Internet of Things. Security and Privacy, 3(3), p.e99.