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.

 

Yongyi Yan | Computer Science and Artificial Intelligence | Best Researcher Award

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Prof. Dr. Yongyi Yan | Computer Science and Artificial Intelligence | Best Researcher Award

Henan University of Science and Technology | China

Prof. Dr. Yongyi Yan, Professor of Control Science at Henan University of Science and Technology, has devoted over 15 years to advancing robust control and intelligent optimization for industrial and autonomous systems, demonstrating a rare blend of theoretical excellence and practical impact. He has authored 65 publications, including influential articles in IEEE Transactions on Automation Science and Engineering and SCIENCE CHINA Information Sciences, accumulating 506 citations with an h-index of 10, reflecting his work’s high recognition and application in both academia and industry. Professor Yan has led multiple National Natural Science Foundation of China projects (U1804150, 62073124, 12571584), supervised three PhD graduates, and served as associate editor for Control Engineering Practice. His pioneering contributions include an adaptive robust control algorithm that reduces oscillation by 40% in high-precision machining and an AI-driven optimization framework (patents ZL2021 1 0419210.4 and ZL202110418903.1) that decreases energy consumption by 18% in automotive assembly lines, now adopted by leading manufacturers. His collaborations with Luoyang Sanwu Cable Group have resulted in significant breakthroughs in high-conductivity aluminum stranded wire cable production, integrating multi-machine coordination, dynamic compensation, and laser-guided visual positioning to enhance efficiency, product quality, and equipment control. By bridging fundamental research with industrial applications, Professor Yan has advanced smart manufacturing, autonomous navigation, and process optimization. His sustained innovation, leadership, and scholarly achievements exemplify research excellence, making him highly deserving of the Best Researcher Award for transformative contributions to control science and engineering.

Profile: Scopus

Featured Publications

  • Li, X., Yan, Y., Yue, J., & Zhang, S. (2025, September). Algebraic insight into universal logic functions and implications for logical system modeling.

  • An, Z., Yan, Y., Yue, J., & Li, X. (2025, May). Construction of automaton observer based on matrix semi-tensor product. In Conference proceedings.

  • Wang, X., Yan, Y., Yue, J., & An, Z. (2025, May). Construction and synchronization analysis of state power set automata based on algebraic methods. In Conference proceedings.

  • Dong, C., Yan, Y., Li, H., & Yue, J. (2024, November). Semi-tensor product approach to controllability, reachability, and stabilizability of extended finite state machines.

  • Zhang, S., Yan, Y., Hao, P., & Yue, J. (2024, October). Structural simplification of finite state machines using pruning operators based on semi-tensor product of matrices. In Conference proceedings.

  • Zhang, S., Yan, Y., Wang, C., & Yue, J. (2024, October). Implementation of automaton product networks: From formal language to algebraic models. In Conference proceedings.

  • Yan, Y., Hao, P., Yue, J., & Feng, J. (2024, October). An STP look at logical blocking of finite state machines: Formulation, detection, and search.

  • Yan, Y., Dong, C., Li, H., & Yue, J. (2024, July). Algebraic implementation of extended finite state machine networks.