Amirhossein Karamoozian | Civil Engineering | Best Researcher Award

Dr. Amirhossein Karamoozian | Civil Engineering | Best Researcher Award

Shenzhen University | China

Dr. Amirhossein Karamoozian is a researcher and lecturer at the International College, University of Chinese Academy of Sciences (UCAS), with a Ph.D. in Management Science and Engineering (Project Management). His research focuses on risk assessment, project management, sustainable construction, and decision-making methodologies, with applications in construction, renewable energy, and transportation projects. He has authored numerous high-impact SCI journal articles and holds multiple patents on construction project risk assessment and material selection. Dr. Karamoozian has received several awards, including best paper recognitions at IEEE symposiums and the UCAS Excellent International Graduate Student Award, reflecting his significant contributions to engineering management research.

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Featured Publications


Assessing urban outdoor thermal discomfort across scales and climates: Implications for sustainable urban management in Iran

– Sustainable Cities and Society, 2026-01Contributors: Aminreza Karamoozian; Abouzar Gholamalizadeh; Saman Nadizadeh Shorabeh; Amirhossein Karamoozian; Mohammad Karimi Firozjaei

COVID-19 automotive supply chain risks: A manufacturer-supplier development approach

– Journal of Industrial Information Integration, 2024-03Contributors: Aminreza Karamoozian; Chin An Tan; Desheng Wu; Amirhossein Karamoozian; Saied Pirasteh

An Integrated Approach for Instability Analysis of Lattice Brake System Using Contact Pressure Sensitivity

– IEEE Access, 2020Contributors: Aminreza Karamoozian; Haobin Jiang; Chin An Tan; Liangmo Wang; Yuanlong Wang

Probability Based Survey of Braking System: A Pareto-Optimal Approach

– IEEE Access, 2020Contributors: Aminreza Karamoozian; Haobin Jiang; Chin An Tan

Chao Li | Data Processing | Research Excellence Award

Dr. Chao Li | Data Processing | Research Excellence Award

Qingdao Technical College | China

Dr. Chao Li is an engineering scholar and lecturer whose work bridges professional education and applied research in advanced sensing technologies. He holds a doctoral degree in engineering and completed his undergraduate studies in industrial equipment and control engineering, where he built a strong foundation in intelligent systems. Since 2019, he has focused extensively on indoor mapping and positioning, integrating theoretical innovation with engineering-driven problem-solving. His research experience includes serving as a core contributor to multiple provincial key R&D initiatives and collaborations with major technology enterprises, where he helped develop applied solutions for real-world industrial environments. He has published several SCI-indexed journal articles as a first or corresponding author and holds an invention patent that reflects the practical impact of his work. In addition to research, he is dedicated to teaching and curriculum development in professional courses, promoting hands-on learning and interdisciplinary thinking. His academic achievements demonstrate a commitment to advancing positioning technologies, enhancing industry–academia collaboration, and addressing emerging challenges in smart manufacturing and intelligent monitoring. Looking ahead, he aims to continue deepening his contributions to indoor mapping and positioning, driving innovation that supports both scientific development and technological progress.

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Featured Publications

Li, C., Chai, W., Zhang, M., Sun, Z., Shao, G., & Li, Q. (2023). “A novel visual-aided method to enhance the inertial navigation system of an intelligent vehicle in indoor environments.” IEEE Transactions on Instrumentation and Measurement. https://doi.org/10.1109/TIM.2023.3293884

Chai, W., Li, C., & Li, Q. (2023). “Multi-sensor fusion-based indoor single-track semantic map construction and localization.” IEEE Sensors Journal. https://doi.org/10.1109/JSEN.2022.3226821

Li, C., Chai, W., Wu, Q., Li, J., Lin, F., Li, Z., & Li, Q. (2022). “A graph optimization enhanced indoor localization method.” In 2022 International Conference on Computers, Information Processing and Advanced Education (CIPAE). https://doi.org/10.1109/cipae55637.2022.00055

Li, C., Chai, W., Yang, X., & Li, Q. (2022). “Crowdsourcing-based indoor semantic map construction and localization using graph optimization.” Sensors. https://doi.org/10.3390/s22166263

Chai, W., Li, C., Zhang, M., Sun, Z., Yuan, H., Lin, F., & Li, Q. (2021). “An enhanced pedestrian visual-inertial SLAM system aided with vanishing point in indoor environments.” Sensors. https://doi.org/10.3390/s21227428