Bingqin Han | Computer Science and Artificial Intelligence | Research Excellence Award

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Mr. Bingqin Han | Computer Science and Artificial Intelligence | Research Excellence Award

Tianjin University | China

Mr. Bingqin Han, is a leading researcher at the intersection of artificial intelligence, consumer psychology, and business ethics, focusing on the factors that influence AI adoption in both consumer and managerial contexts. His work integrates behavioral science, marketing, and technology studies to examine how trust, risk perception, ethical considerations, and cognitive biases shape the acceptance and utilization of AI technologies. He has pioneered innovative frameworks for modeling human–AI interaction, most notably the “onion model” of AI humanoid robot adoption in domestic settings, which conceptualizes acceptance across technical, psychological, and social layers, offering both theoretical and practical insights. Mr. Bingqin Han’s scholarly contributions include three peer-reviewed publications, which have garnered three citations and an h-index of 1 according to Scopus, reflecting his emerging influence in the field. Beyond publications, he has contributed to interdisciplinary research projects, participated in editorial and peer-review activities, and engaged in collaborative initiatives that bridge academia and industry, highlighting his commitment to advancing both theory and practice. His work has significantly enriched understanding of human–AI integration, providing actionable guidance for developers, policymakers, and researchers aiming to optimize AI deployment in real-world environments. By combining rigorous empirical research, innovative conceptual frameworks, and interdisciplinary collaboration, Han has made substantial contributions to AI adoption research, behavioral decision-making, and ethical technology development, establishing a foundation for future innovations and informing responsible, human-centered implementation of AI technologies across diverse contexts.

Profile: Scopus

Featured Publications

  • Han, B., Song, S., Liu, D., & Mo, J. (2024). Mechanism of online public opinion formation in major risk events in China: A qualitative comparative analysis.

  • Han, B., & Liu, D. (2025). Peeling back acceptance: An onion model of AI humanoid robot adoption in homes.

 

Mahmoud Abd-Ellah | Computer Science | Best Researcher Award

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Assoc. Prof. Dr. Mahmoud Abd-Ellah | Computer Science | Best Researcher Award

Egyptian Russian University | Egypt

Dr. Mahmoud Khaled Abd-Ellah is an accomplished Assistant Professor at the Faculty of Artificial Intelligence, Egyptian Russian University, Badr, Egypt, widely recognized for his pioneering research at the intersection of artificial intelligence, medical imaging, and deep learning. Holding a Ph.D. in Electrical Engineering from Minia University, his doctoral research focused on brain tumor diagnosis through MRI using advanced machine learning techniques. His impressive publication portfolio includes 22 Scopus-indexed papers, collectively cited 830 times by 774 documents, with an h-index of 12 demonstrating substantial scientific impact and research excellence. His scholarly work has been featured in leading journals such as Scientific Reports, Neural Computing and Applications, and Ecological Informatics, advancing AI-driven approaches for medical image analysis, automated brain tumor detection, COVID-19 classification, and environmental data modeling. Beyond research, Dr. Abd-Ellah actively contributes to academic governance and quality enhancement as a member of the Egyptian International Ranking Committee, head of the Quality Management Unit, and ranking official at the Egyptian Russian University. He is also an active member of multiple IEEE councils, engaging in the development and application of AI across engineering and biomedical domains. His ORCID profile (0000-0002-6840-2503) and Scopus ID (57191265348) further reflect his consistent record of impactful scholarship and international collaboration. With his interdisciplinary expertise, editorial service, and mentorship of Ph.D. and master’s students, Dr. Mahmoud Khaled Abd-Ellah exemplifies academic leadership, innovation, and a transformative approach to research that advances both science and society.

Profile: Scopus | Google Scholar | ORCID | ResearchGate

Featured Publications

  • Abd-Ellah, M. K., Awad, A. I., Khalaf, A. A. M., & Hamed, H. F. A. (2019). A review on brain tumor diagnosis from MRI images: Practical implications, key achievements, and lessons learned. Magnetic Resonance Imaging, 61, 300–318.

  • Abd-Ellah, M. K., Awad, A. I., Khalaf, A. A. M., & Hamed, H. F. A. (2018). Two-phase multi-model automatic brain tumour diagnosis system from magnetic resonance images using convolutional neural networks. EURASIP Journal on Image and Video Processing, 2018(1), 1–10.

  • El-Rawy, M., Abd-Ellah, M. K., Fathi, H., & Ahmed, A. K. A. (2021). Forecasting effluent and performance of wastewater treatment plant using different machine learning techniques. Journal of Water Process Engineering, 44, 102380.

  • Abd-Ellah, M. K., Awad, A. I., Khalaf, A. A. M., & Hamed, H. F. A. (2016). Design and implementation of a computer-aided diagnosis system for brain tumor classification. In 2016 28th International Conference on Microelectronics (ICM) (pp. 73–76).

  • MostafaShokry, A. A. M. K., Awad, A. I., & Abd-Ellah, M. K. (2022). Systematic survey of advanced metering infrastructure security: Vulnerabilities, attacks, countermeasures, and future vision. Future Generation Computer Systems, 1–21.