Assistant Professor, Imam Mohammad Ibn Saud Islamic University (IMSIU), Saudi Arabia
Dr. Waeal J. Obidallah 🌍 is a dynamic researcher and academician with over a decade of expertise in both corporate and academic realms. With a rich blend of experience in digital transformation, machine learning, data mining, and electronic business technologies, Dr. Obidallah has continually driven innovative outcomes in every role he has undertaken. Known for his leadership in guiding cross-functional teams and for his analytical mindset, he seamlessly bridges the gap between research theory and practical application. His inspiring approach, commitment to growth, and passion for pushing boundaries make him a prominent figure in the fields of digital innovation and intelligent systems.
Publication Profile
🎓 Education Background
Dr. Obidallah earned his Ph.D. in Digital Transformation and Innovation from the University of Ottawa, Canada 🇨🇦 (2014–2021), where he developed cutting-edge expertise in leveraging technology for transformative change. He previously completed his MSc in Electronic Business Technologies at the same university (2011–2013), equipping him with a solid foundation in the digital economy, e-commerce, and business intelligence systems.
💼 Professional Experience
Currently serving as an Assistant Professor at the Imam Mohammad ibn Saud Islamic University in Riyadh, Saudi Arabia 🇸🇦 since 2021, Dr. Obidallah has been instrumental in shaping curriculum and guiding research in the College of Computer and Information Sciences, Department of Information Systems. His professional background includes leading interdisciplinary teams in both academia and industry, delivering data-driven solutions and high-impact publications.
🏅 Awards and Honors
While no individual awards are listed, Dr. Obidallah’s profile is marked by significant academic impact 📈, evidenced by over 100+ citations, 54 co-authors, and contributions to renowned international journals. His consistent scholarly output reflects recognition and respect within the global research community.
🔬 Research Focus
Dr. Obidallah’s research focuses on Digital Transformation, Data and Text Mining, Machine Learning, FinTech, Blockchain, and Big Data 📊. He is especially interested in applying AI and data science techniques to enhance intelligent systems, industrial operations, medical sensors, and smart environments. His work also incorporates Design Science Research Methodology (DSRM) to structure innovation with academic rigor.
🧩 Conclusion
A lifelong learner and dedicated innovator, Dr. Waeal Obidallah continues to influence the evolving landscape of data-driven technologies with his deep expertise and enthusiastic leadership. 🚀 His unwavering pursuit of excellence, coupled with his motivational spirit, has made him a role model for aspiring researchers and collaborators alike. Embracing challenges beyond the comfort zone, he is committed to making impactful contributions in the ever-changing digital world.
📚 Top Publication Notes
Quantum computational infusion in extreme learning machines for early multi-cancer detection – Journal of Big Data, 2025
Cited by: 1 | This innovative article explores the fusion of quantum computing with ELMs to revolutionize early cancer diagnostics.
Deep learning based approaches for intelligent industrial machinery health management and fault diagnosis in resource-constrained environments – Scientific Reports, 2025
Cited by: 2 | A comprehensive study of deep learning models designed for predictive maintenance in limited-resource industrial setups.
AI-based energy aware parent selection mechanism to enhance security and energy efficiency for smart homes in IoT – Expert Systems, 2025
A novel AI-powered method optimizing security and energy in IoT home systems.
DOI: 10.1111/exsy.13647
Beyond the hype: A TAM-based analysis of blockchain adoption drivers in construction industry – Heliyon, 2024
Offers insights into real-world blockchain adoption using the Technology Acceptance Model (TAM).
DOI: 10.1016/j.heliyon.2024.e38522
Ensuring the integrity assessment of IoT medical sensors using hesitant fuzzy sets – Health Informatics Journal, 2024
Focuses on trustworthy IoT applications in healthcare via fuzzy logic.
DOI: 10.1177/14604582241301019
Intelligent Reconfigurable Surface Assisted Constellation Index Selection Spatial Modulation Over Nakagami-m Fading Channels – IEEE Access, 2024
Technical exploration of smart communication channels with reconfigurable surfaces.
DOI: 10.1109/ACCESS.2024.3455998