Shadi Shayan | Emerging Technologies | Best Researcher Award

Dr. Shadi Shayan | Emerging Technologies | Best Researcher Award

Dr. Shadi Shayan | Adelaide University | Australia

Dr. Shadi Shayan’s research lies at the intersection of project management, smart technologies, and social sustainability, focusing on how large-scale urban innovation programs can effectively manage social risks and deliver equitable outcomes. His scholarly work explores the dynamic relationships between technological transformation, social response, and governance frameworks in smart city development. By integrating change management models with risk management processes, Dr. Shayan has developed innovative frameworks that address the socio-demographic dimensions of smart city transitions—bridging theory, practice, and policy. His doctoral research, “Integrating change models and risk management processes: A framework to manage social risks in smart city programs”, provides a comprehensive model for mitigating community resistance and fostering inclusive participation in technologically driven urban initiatives. Dr. Shayan’s publications in leading journals such as Smart Cities, Sustainable Cities and Society, and International Journal of Construction Management advance understanding of how social factors, demographic variables, and stakeholder perceptions influence the success of smart city and infrastructure projects. A consistent theme in his research is the application of systems thinking and socio-technical analysis to enhance decision-making in project and program management. He also examines the evolving roles of professionals, including engineers and quantity surveyors, in adapting to emerging technological and societal challenges. Dr. Shayan’s work has significant implications for both academia and industry. It informs policy frameworks for smart urban governance, supports organizational strategies for managing social risk, and contributes to sustainable and resilient infrastructure planning. Through interdisciplinary collaborations and active engagement with the Smart Cities Council Australia New Zealand, he connects research with real-world impact—helping shape cities that are not only technologically advanced but also socially responsible and inclusive.

Profiles: Google Scholar | LinkedIn

Featured Publications 

Shayan, S., & Kim, K. P. (2025). Social responses and change management strategies in smart city transitions: A socio-demographic perspective. Smart Cities, 8(6), 188. https://doi.org/10.3390/smartcities8060188

Shayan, S., & Kim, K. P. (2023). Understanding correlations between social risks and sociodemographic factors in smart city development. Sustainable Cities and Society, 89, 104320. https://doi.org/10.1016/j.scs.2022.104320

Shayan, S., & Kim, K. P. (2022). A conceptual framework to manage social risks for smart city development programs. In Resilient and responsible smart cities (pp. 77–86). Springer, Cham. https://doi.org/10.1007/978-3-030-98423-6_6

Shayan, S., Kim, K. P., Ma, T., & Nguyen, T. H. D. (2020). The first two decades of smart city research from a risk perspective. Sustainability, 12(21), 9280. https://doi.org/10.3390/su12219280

Shayan, S., & Kim, K. P., & Tam, V. (2019). Critical success factor analysis for effective risk management at the execution stage of a construction project. International Journal of Construction Management, 22(3), 379–386. https://doi.org/10.1080/15623599.2019.1624678

Bao Liu | Emerging Technologies | Best Researcher Award

Dr. Bao Liu | Emerging Technologies | Best Researcher Award

Dr. Bao Liu | Xi’an University of Science and Technology | China

Dr. Liu Bao is an Associate Professor and Academic Leader in the field of Pattern Recognition and Intelligent Systems at the School of Electrical and Control Engineering, Xi’an University of Science and Technology, where he also serves as a Graduate Supervisor and Project-based Ph.D. Supervisor. He earned his doctorate in engineering from Xi’an Jiaotong University, completed postdoctoral research at Xi’an University of Science and Technology, and broadened his academic experience as a visiting fellow at Macquarie University in Australia. Recognized as a Senior Data Analyst by the Ministry of Industry and Information Technology of China, Dr. Liu is an active member of several national academic societies and professional committees. His research focuses on multi-source information fusion and intelligent technologies for coal fire disaster prevention and control, integrating advanced computational and automation techniques to address complex industrial challenges. Throughout his career, he has led diverse national, provincial, and industry-based research projects and contributed extensively to scientific publications and technological innovation through patents and software developments. As a committed educator and mentor, Dr. Liu has inspired students to excel in academic and professional pursuits and has been honored with multiple awards recognizing his dedication to teaching, research, and academic service.

Profile: Orcid

Featured Publications

Liu, B., Liu, Q., & Wu, Z. (2026, February). A novel robust Student’s t scale mixture distribution based Kalman filter. Signal Processing. https://doi.org/10.1016/j.sigpro.2025.110296

Liu, B., Wu, Z., & Liu, Q. (2025). Gaussian mixture model-based variational Bayesian approach for extended target tracking. IEEE Transactions on Instrumentation and Measurement. https://doi.org/10.1109/TIM.2025.3565347

Liu, B., & Jiang, W. (2024). DFKD: Dynamic focused knowledge distillation approach for insulator defect detection. IEEE Transactions on Instrumentation and Measurement. https://doi.org/10.1109/TIM.2024.3485446

Liu, B., & Jiang, W. (2024, December). LA-YOLO: Bidirectional adaptive feature fusion approach for small object detection of insulator self-explosion defects. IEEE Transactions on Power Delivery. https://doi.org/10.1109/TPWRD.2024.3467915

Liu, B., Zhou, N., & Wang, Z. (2024, December 27). DFI-YOLOv8 based defect detection method for fan blades. In Proceedings of the 2024 Conference on [Insert Conference Name]. https://doi.org/10.1145/3722405.3722437