Mr. Li Xiao | Engineering | Best Industrial Research Award

Northwest Normal University | China

Mr. Li Xiao, in Lanzhou, Gansu Province, China, is a dedicated researcher currently pursuing a master’s degree at Northwest Normal University after completing his undergraduate studies at Anyang Normal University . Throughout his academic journey, he has demonstrated exceptional excellence, earning multiple scholarships including the National Encouragement Scholarship, school-level scholarships, and awards such as the third prize  Lanqiao Algorithm Competition for University Group B and the Third Prize Team Award in the Computer Competition for Chinese Universities – Programming Ascension Contest in Henan Province. Professionally, Li Xiao has actively engaged in research projects, notably securing Annual Research Funding Project at Northwest Normal University, and has contributed to publications including a paper titled “Industrial Prediction Method Based on Graph Sampling and Aggregation of Temporal Features” in The Canadian Journal of Chemical Engineering. His research interests center on industrial prediction methods, algorithmic modeling, and the application of computational techniques to solve practical engineering challenges. Li Xiao has developed strong research skills in data analysis, temporal feature aggregation, graph-based sampling methods, and predictive modeling, reflecting a robust ability to integrate theoretical frameworks with real-world industrial applications. Beyond technical expertise, he has demonstrated leadership and collaboration skills through team competitions and research projects, positioning him as an emerging leader in engineering research. His awards and honors underscore both his academic excellence and innovative contributions to the field. In conclusion, Mr. Li Xiao’s consistent achievements, research capabilities, and proactive engagement in scholarly and industrial projects make him a highly deserving recipient of the Best Industrial Research Award, as his work not only advances engineering research but also promises significant impact on industrial practices and global scientific collaboration.

Profile: Orcid

Featured Publications

Gao, S., Li, X., Yang, W., Xie, J., & Yun, P. (2025). Industrial prediction method based on graph sampling and aggregation of temporal features. The Canadian Journal of Chemical Engineering. Advance online publication.