Assistant Professor

PhD in Electrical and Computer Engineering, University of Waterloo, 2018

Bio

Dr. Hayawi earned his PhD in Electrical and Computer Engineering from the University of Waterloo and an MSc in Computer Science from Dalhousie University, Canada. Before joining the College of Interdisciplinary Studies, focusing on Computational Systems, he was the Graduate Program Coordinator at Zayed University and also contributed his expertise at the United Arab Emirates University. With over two decades of experience across academia and industry, Dr. Hayawi holds numerous prestigious industry certifications. He has provided numerous innovative open-source datasets and source codes to both the research and professional communities. His research, grounded in Machine Learning, NLP, Data Science, and Blockchain Technologies, addresses key challenges in Cybersecurity, Social Bot Detection, IoT, Cloud Computing, and Digital Health. His research findings have been featured in leading journals and conferences such as IEEE IoT, IEEE OJ-COMS, Vaccines, Neural Computing and Applications, Public Health, ICWS, ADMA, AINA, IWCMC, and AICCSA.

 
Office

Abu Dhabi - Khalifa City, MF3-02-008

Phone:

+971 2 599 3545

Email:
Teaching Areas

Cybersecurity, Machine Learning, NLP, Healthcare Data Analytics, and Blockchain

Research and Professional Activities

1. Hayawi, K., Anwar, Z., Malik, A. W., & Trabelsi, Z. (2023). Airborne Computing: A Toolkit for UAV-Assisted Federated Computing for Sustainable Smart Cities. IEEE Internet of Things Journal.

2. Hayawi, K., Saha, S., Masud, M. M., Mathew, S. S., & Kaosar, M. (2023). Social media bot detection with deep learning methods: a systematic review. Neural Computing and Applications, 35(12), 8903-8918.

3. Serhani, M. A., Abreha, H. G., Tariq, A., Hayajneh, M., Xu, Y., & Hayawi, K. (2023). Dynamic Data Sample Selection and Scheduling in Edge Federated Learning. IEEE Open Journal of the Communications Society.

4. Hayawi, K., Mathew, S., Venugopal, N., Masud, M. M., & Ho, P. H. (2022). DeeProBot: a hybrid deep neural network model for social bot detection based on user profile data. Social Network Analysis and Mining, 12(1), 43.

5. Hayawi, K., Shahriar, S., Serhani, M. A., Taleb, I., & Mathew, S. S. (2022). ANTi-Vax: a novel Twitter dataset for COVID-19 vaccine misinformation detection. Public Health, 203, 23-30.

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