Zhiqi Wu | Engineering | Best Researcher Award

Published on by Innovation Technologist

Ms. Zhiqi Wu | Engineering | Best Researcher Award

Student at Anhui University of Science and Technology | China

Zhiqi Wu is a Master’s student in Electrical Engineering at Anhui University of Science and Technology, specializing in computer vision applications for intelligent coal gangue detection. His research emphasizes developing lightweight, high-performance models that improve automation and efficiency in mining operations. Zhiqi proposed a novel model integrating multispectral imaging with knowledge distillation, achieving a precision increase of up to 6% while reducing model size by 21.8%, enabling deployment on mobile and edge devices for real-time sorting. This approach advances intelligent coal industry practices by combining computational efficiency with practical industrial applicability. Zhiqi’s work exemplifies the translation of advanced AI techniques into actionable solutions for industrial automation, with a focus on scalability, accuracy, and sustainability. His contributions are recognized in the research community, with 1 citation for his published work, highlighting its impact and relevance. To date, he has contributed to 4 documents in his research portfolio, reflecting his engagement in ongoing innovation and knowledge dissemination. While his h-index currently stands at 1, it represents a promising start in a career dedicated to applied AI in mining technologies. Zhiqi continues to explore methods for optimizing computer vision systems in industrial contexts, advancing automation, operational safety, and resource efficiency. His work bridges theoretical research and practical deployment, positioning him as an emerging researcher making measurable contributions to intelligent mining technologies.

Profile: Scopus

Featured Publications

Yan, P. (2025). Transformer fault diagnosis based on LIF technology and COA-GRU algorithm. Engineering Research Express, 7(2), 25409.

Jingcai Yu | Transportation | Best Researcher Award

Published on by Innovation Technologist

Dr. Jingcai Yu | Transportation | Best Researcher Award

lecturer at Xihua University, China

Dr. Jingcai Yu is a dedicated transportation engineer and researcher with expertise in public transportation and traffic safety. He earned his Doctor of Engineering degree from Southeast University’s School of Transportation, where he specialized in travel behavior modeling and transit adoption studies. Currently based at Xihua University in Chengdu, China, Dr. Yu has published extensively in peer-reviewed journals, contributing valuable insights into the effects of attitudes, sociodemographic factors, and traffic conditions on transit and mobility choices. His work addresses emerging challenges in urban mobility, particularly through studies on flexible transit routes and shared autonomous vehicles, highlighting his commitment to advancing sustainable and efficient transportation solutions.

Publication Profile : 

Scopus

 

🎓 Educational Background :

Dr. Jingcai Yu completed his Doctorate in Engineering in Transportation at the School of Transportation, Southeast University, China. His doctoral research focused on public transportation, travel behavior modeling, and traffic safety, areas in which he has since made numerous academic contributions.

💼 Professional Experience :

Dr. Yu is currently based at Xihua University in Chengdu, China, where he holds an academic position. He engages in teaching, research, and academic mentorship, primarily within the field of transportation engineering. Through his role at Xihua University, Dr. Yu applies his expertise in public transit systems, travel behavior analysis, and transportation safety to help address urban mobility challenges. His work includes investigating the factors influencing the adoption of flexible route transit systems, carsharing, and shared autonomous vehicles. Dr. Yu’s research outputs, published in prestigious journals, have significantly contributed to the fields of transportation safety, autonomous vehicle studies, and public transit utilization.

📚 Research Interests : 

Dr. Jingcai Yu’s research interests encompass public transportation systems, travel behavior modeling, and traffic safety. He focuses on innovative transit solutions such as flex-route transit systems, shared autonomous vehicles, and carsharing. His work also investigates factors affecting crash severity and traffic violations, as well as advanced prediction models for urban traffic flow.

📝 Publication Top Notes :

  1. Yu, J., Wang, S., Wang, B., Li, W., & Feng, T. (2024). Effects of COVID-19 on Flex Route Transit Utilization: An Interrupted Time Series Analysis. Research in Transportation Business & Management, 50, 101230.
  2. Yu, J., Li, W., Yin, Z., Zheng, Y., & Guo, R. (2024). Segmenting and exemplifying potential Flex route transit adopters. Transportation Research Record, 2678(9), 791-806. (SCI)
  3. Yu, J., Lin, Q., Ding, H., Li, W., & Feng, T. (2024). Examining individuals’ adoption of flex route transit. Transportation Planning and Technology, 47(7), 996-1021. (SCI)
  4. Yu, J., Li, W., Song, Z., Wang, S., Ma, J., & Wang, B. (2023). The role of attitudinal features on shared autonomous vehicles. Research in Transportation Business & Management, 50, 101032. (SCI)
  5. Yu, J., Wang, S., Ma, J., Song, Z., & Li, W. (2023). Roles of attitudinal factors on the adoption stages of carsharing. Transportation Letters, 16(6), 542-553. (SCI)
  6. Yu, J., Zheng, Y., Li, W., Zhang, J., Guo, R., & Wu, L. (2023). Understanding Flex-Route Transit Adoption from a Stage of Change Perspective. Transportation Research Record, 2677(6), 743-758. (SCI)
  7. Yu, J., Li, W., Zhang, J., Guo, R., & Zheng, Y. (2023). Understanding the effect of sociodemographic and psychological latent characteristics on flex-route transit acceptance. PLOS ONE, 18(2), e0279058. (SCI)
  8. Wang, S., Yu, J.*, & Ma, J. (2023). Identifying the heterogeneous effects of road characteristics on Motorcycle-Involved crash severities. Travel Behaviour and Society, 33, 100636. (SCI)
  9. Ma, J., Ren, G., Li, H., & Yu, J. (2022). Characterizing the differences of injury severity between single-vehicle and multi-vehicle crashes in China. Journal of Transportation Safety & Security, 1-21. (SCI)
  10. Wang, S., Li, Z., Wang, B., & Yu, J. (2022). Velocity obstacle-based collision avoidance and motion planning framework for connected and automated vehicles. Transportation Research Record, 2676(5), 748-766. (SCI)
  11. Zheng, Y., Wang, S., Li, W., & Yu, J. (2022). Urban road traffic flow prediction: A graph convolutional network embedded with wavelet decomposition and attention mechanism. Physica A: Statistical Mechanics and its Applications, 608, 128274. (SCI)
  12. Ma, J., Ren, G., Wang, S., & Yu, J. (2022). Characterizing the effects of contributing factors on crash severity involving e-bicycles: A study based on police-reported data. International Journal of Injury Control and Safety Promotion, 29(4), 463-474. (SCI)
  13. Ma, J., Ren, G., Fan, H., Wang, S., & Yu, J. (2021). Determinants of traffic violations in China: A case-study with a partial proportional odds model. Journal of Transportation Safety & Security, 1-21. (SCI)