Dr. Waeal Obidallah | Blockchain Technology | Best Researcher Award

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Dr. Waeal Obidallah | Blockchain Technology | Best Researcher Award

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

 

 

Masabah Bint E Islam | Blockchain | Best Researcher Award

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Ms. Masabah Bint E Islam | Blockchain | Best Researcher Award

Graduate, SEECS NUST, Pakistan

MBE Islam is a dedicated researcher and academic specializing in artificial intelligence, machine learning, and healthcare informatics. With a strong background in computational sciences, he has contributed significantly to interdisciplinary research, particularly in medical data analytics and blockchain-based security frameworks. His research integrates AI-driven models with real-world applications, such as disease classification, water quality monitoring, and deepfake detection. His scholarly contributions in top-tier journals and conferences underscore his expertise in the field.

Publication Profile

Education 🎓

MBE Islam has pursued a rigorous academic journey in the domain of artificial intelligence and computational sciences. He holds advanced degrees in computer science and machine learning, equipping him with the skills necessary to address complex data-driven challenges. His research focuses on integrating AI and data mining techniques in healthcare analytics and cybersecurity.

Experience 🏢

With a wealth of experience in both academia and industry, MBE Islam has worked on various AI-based projects, including disease prediction models, blockchain security, and automated classification systems. His collaborations with renowned institutions and research groups have resulted in groundbreaking studies published in high-impact journals and international conferences. He has also been actively involved in teaching, mentoring, and supervising students in AI, machine learning, and data analytics.

Awards and Honors 🏆

Throughout his career, MBE Islam has been recognized for his outstanding contributions to AI and healthcare analytics. His research publications have received citations from esteemed scholars worldwide. His work on blockchain-based authenticity verification and AI-driven disease classification has been acknowledged for its innovation and impact.

Research Focus 🔬

MBE Islam’s research spans multiple domains, including AI in healthcare, blockchain security, and computational biology. His work on supervised machine learning for comorbidity analysis, association rule mining for IBS patients, and deepfake authenticity verification using blockchain highlights his interdisciplinary approach. He has also explored AI-based water quality assessment and lung disease classification, showcasing his ability to apply computational techniques to real-world challenges.

Conclusion 🌟

MBE Islam is a trailblazing researcher whose work bridges AI, healthcare, and security. His contributions to disease classification, blockchain security, and medical AI applications have made a significant impact on academia and industry. His research continues to shape the future of AI-driven healthcare solutions and secure digital systems. 🚀

Publication📚

Identifying comorbidity patterns of irritable bowel syndrome (IBS) patients using association rule mining (2023) – Neurogastroenterology and Motility

AI threats to politics, elections, and democracy: A blockchain-based deepfake authenticity verification framework (2024) – Blockchains Journal

From Measured pH to Hidden BOD: Quasi Real-Time Estimation of Key Indirect Water Quality Parameters Through Direct Sensor Measurements (2024) – ICICT Proceedings

Classification of Lung Diseases Through Artificial Intelligence Models: A Multi-Dataset Evaluation (2024) – IEEE International Conference on Signal Processing

Supervised machine learning analysis of comorbidities in irritable bowel syndrome: A UK BioBank Study (2023) – Neurogastroenterology and Motility

Mr. Mohammad Naderi | Vehicular Communications | Smart Cities Technologies Award

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Mr. Mohammad Naderi | Vehicular Communications | Smart Cities Technologies Award

Part-time lectrutre, self-employed, Iran

Mohammad Naderi is a dedicated computer engineer and researcher from Iran, specializing in wireless communications and networking. With a strong academic background and practical expertise, he has contributed significantly to the fields of the Internet of Things (IoT), Vehicular Ad Hoc Networks (VANETs), Mobile Ad Hoc Networks (MANETs), and Software-Defined Networking (SDN). His innovative approaches to opportunistic routing and traffic-aware networking solutions have led to impactful publications in high-ranking journals. Alongside his research, he has mentored master’s and Ph.D. students, providing guidance in simulation and network-related studies.

Publication Profile

🎓 Education

Mohammad Naderi pursued his Bachelor of Science (BSc) in Computer Engineering at Hamedan University of Technology, Iran, graduating in 2013. He continued his academic journey with a Master of Science (MSc) in Computer Engineering from Azad University, Science and Research Branch, Tehran, where he achieved an outstanding GPA of 3.44. His academic excellence placed him among the top 15 national rank holders, reflecting his strong grasp of computational and networking concepts.

💼 Experience

With a passion for both academia and practical research, Mohammad Naderi has served as an advisor and lecturer, guiding master’s and Ph.D. students in IoT, VANETs, MANETs, UAV Communications, and SDN Security. Since 2016, he has been actively involved in mentoring students, helping them develop innovative research ideas and simulation models. Additionally, he has worked as a part-time lecturer at Danesh Institute, specializing in NS-2 simulation tools. In 2023, he took on a lecturing role at Islamic Azad University, Pardis Branch, where he taught computer networks and network lab courses, strengthening his expertise in teaching and research.

🏆 Awards and Honors

His exceptional work in computer engineering research earned him the Master of Science Thesis Award from the IEEE Iran Section in May 2019. This prestigious recognition underscores his contributions to the advancement of network communications and routing optimizations.

🔬 Research Focus

Mohammad Naderi’s research primarily revolves around opportunistic routing, VANETs, MANETs, IoT, UAV communications, and software-defined vehicular networks. His work integrates artificial intelligence techniques, including reinforcement learning and fuzzy logic, to optimize vehicular communication protocols. He has also explored hierarchical Q-learning-enabled neutrosophic AHP schemes, adaptive beaconing strategies, and routing efficiency in wireless networks, paving the way for more intelligent and reliable vehicular networking solutions.

🔚 Conclusion

Mohammad Naderi’s expertise in wireless networks, VANETs, SDN, and AI-driven communication systems has positioned him as a leading researcher in the field. His contributions to opportunistic routing and adaptive vehicular networking strategies are highly regarded, making a significant impact on next-generation communication technologies. With a strong commitment to both academic and practical advancements, he continues to push the boundaries of intelligent networking solutions. 🚀

📚 Publications

A 3-Parameter Routing Cost Function for Improving Opportunistic Routing Performance in VANETs – Published in Wireless Personal Communications (2017), this paper explores routing optimizations in VANETs to enhance communication reliability. 🔗 Read more.

Adaptive beacon broadcast in opportunistic routing for VANETs – Featured in Ad Hoc Networks (2019), this study introduces adaptive beaconing techniques to optimize data forwarding efficiency in vehicular environments. 🔗 Read more.

Adaptively prioritizing candidate forwarding set in opportunistic routing in VANETs – Published in Ad Hoc Networks (2023), this research enhances routing protocols using adaptive prioritization mechanisms. 🔗 Read more.

Hierarchical traffic light-aware routing via fuzzy reinforcement learning in software-defined vehicular networks – This 2023 Peer-to-Peer Networking and Applications publication introduces an AI-driven hierarchical traffic-aware routing strategy. 🔗 Read more.

Hierarchical Q-learning-enabled neutrosophic AHP scheme in candidate relay set size adaption in vehicular networks – A Computer Networks (2023) publication that leverages Q-learning and neutrosophic AHP techniques to improve vehicular communication. 🔗 Read more.