Abu Dhabi University | United Arab Emirates
Assoc. Prof. Dr. Modafar Ati is an accomplished academic and researcher in Computer Science and Information Technology with extensive experience in teaching, curriculum development, and leadership. He holds a BSc in Electrical & Communication Engineering and a PhD in Electrical & Computing Engineering from Newcastle upon Tyne, UK. Dr. Ati has over three decades of experience in both academia and industry, serving in senior roles including Associate Professor at Abu Dhabi University, Acting Dean at Sohar University, and Assistant Dean at multiple institutions in Oman. His professional expertise spans software development, systems integration, networking, ICT, project management, Service-Oriented Architecture (SOA), Artificial Intelligence, Big Data, Cybersecurity, and eHealth smart systems. He has published numerous research articles focusing on AI-driven Chronic Disease Management and smart healthcare systems and has led research groups in eGovernment and ICT. Dr. Ati has received multiple grants and awards, including the Chancellor Innovation Award, and serves on editorial boards and as a senior reviewer for international journals and conferences. His teaching portfolio covers programming, network security, project management, human-computer interaction, and mobile application development. Dr. Ati’s contributions to education, research, and innovation reflect a strong commitment to advancing technology-driven solutions in healthcare, smart cities, and digital systems.
Profile : Google Scholar
Featured Publications
Hussein, A. S., Omar, W. M., Li, X., & Ati, M. (2012). “Efficient chronic disease diagnosis prediction and recommendation system” in 2012 IEEE-EMBS Conference on Biomedical Engineering and Sciences, 209–214.
Mohamed, O., Kewalramani, M., Ati, M., & Al Hawat, W. (2021). “Application of ANN for prediction of chloride penetration resistance and concrete compressive strength” in Materialia, 17, 101123.
Mohamed, O. A., Ati, M., & Najm, O. F. (2017). “Predicting compressive strength of sustainable self-consolidating concrete using random forest” in Key Engineering Materials, 744, 141–145.
Hussein, A. S., Omar, W. M., Li, X., & Ati, M. (2012). “Accurate and reliable recommender system for chronic disease diagnosis” in Global Health, 3(2), 113–118.
Ati, M., Kabir, K., Abdullahi, H., & Ahmed, M. (2018). “Augmented reality enhanced computer aided learning for young children” in 2018 IEEE Symposium on Computer Applications & Industrial Electronics.