Yi Liu | Data Science and Deep Learning | Research Excellence Award

Prof. Yi Liu | Data Science and Deep Learning | Research Excellence Award

Leader at Hangzhou Dianzi University | China

Prof. Yi Liu is a Professor in the Department of Information Management and Information Systems at Hangzhou Dianzi University, China, and a visiting scholar at leading international institutions, whose research integrates management science, digital economy, intelligent optimization algorithms, information systems, and econometric modeling, with significant scholarly contributions through influential books, high-impact SCI/SSCI publications, national research projects, patents, and applied innovations advancing traditional manufacturing, digital transformation, and decision-support systems.

Citation Metrics (Scopus)

400

300

200

100

0

Citations
313

Documents
23

h-index
8

🟦 Citations    🟥 Documents    🟩 h-index


View Scopus Profile
           View Orcid Profile

Featured Publications

Binbin Qin | Data Science and Deep Learning | Best Researcher Award

Mr. Binbin Qin | Data Science and Deep Learning | Best Researcher Award

Instructor at Zhejiang Institute of Economics and Trade | China

Binbin Qin is a dedicated academic and researcher currently serving as a lecturer in the School of Business Intelligence at Zhejiang Institute of Economics and Trade, China. His work bridges the dynamic intersections of artificial intelligence, computer vision, and data mining, where he continually explores innovative methodologies that enhance intelligent decision-making and automated learning systems. With a strong focus on applying AI technologies to real-world problems, he contributes to developing intelligent solutions that improve safety, efficiency, and data-driven insights in various domains. His scholarly endeavors are characterized by a deep interest in how computational models can mimic human perception and decision-making through advanced neural network architectures and learning paradigms. Among his notable contributions, his publication titled “Distracted Driver Detection Based on a CNN With Decreasing Filter Size” in the IEEE Transactions on Intelligent Transportation Systems exemplifies his expertise in designing high-performance convolutional neural network frameworks capable of addressing critical safety challenges in intelligent transportation. Through his continuous research, he aims to merge the theoretical foundations of artificial intelligence with practical applications that influence intelligent mobility, human-computer interaction, and predictive analytics. reflects his growing contributions to the research community. As an emerging scholar in the field of computational intelligence, Binbin Qin remains committed to advancing interdisciplinary research that integrates algorithmic innovation with applied data science to drive the future of smart systems, autonomous learning environments, and intelligent business analytics.

Profile: Orcid

Featured Publications:

Qin, B. (2025). CRNet: A driver distraction detection model based on cascaded ResNet networks and attention mechanisms. IET Intelligent Transport Systems.

Qin, B., Qian, J., Xin, Y., Liu, B., & Dong, Y. (2022). Distracted driver detection based on a CNN with decreasing filter size. IEEE Transactions on Intelligent Transportation Systems.