Assoc. Prof. Dr. Shengbin Liang | Data Mining | Excellence in Research Award
Assoc. Prof. Dr. Shengbin Liang | Data Mining | Henan University | China
Assoc. Prof. Dr. Shengbin Liang, a distinguished academic from Henan University, China, has emerged as a leading researcher in the fields of Precision Medicine, Artificial Intelligence, Deep Learning, and Swarm Intelligence Algorithms. He earned his Master’s degree in Computer Science from Southwest Jiaotong University, China, and later obtained his Ph.D. in Data Science from the City University of Macau, China, where he developed a strong foundation in computational modeling and data-driven healthcare applications. Currently, Assoc. Prof. Dr. Shengbin Liang serves as an Associate Professor at Henan University, while also holding a Postdoctoral Fellowship at the University of Saint Joseph, funded by the FDCT, Macau. His professional experience spans interdisciplinary research collaborations that bridge computer science, data science, and medical informatics, focusing on intelligent diagnostic systems and clinical decision-making through machine learning and deep learning frameworks. His research interests encompass recommendation systems, swarm intelligence optimization, biomedical data analysis, medical text classification, and AI-based healthcare prediction models. Demonstrating exceptional research capability, he has published over 20 SCI/EI-indexed papers in reputed international journals and conferences such as IEEE Transactions, PLOS One, Applied Sciences, and Knowledge and Information Systems, earning more than 180 citations on Scopus. His research skills include expertise in Python, TensorFlow, PyTorch, deep neural network architectures, sentiment analysis models, and multimodal data fusion for healthcare applications. In recognition of his academic excellence, Assoc. Prof. Dr. Shengbin Liang has been granted three national invention patents and has received institutional honors for his innovation and scientific contributions. He is also an active member of the IEEE community, contributing to collaborative research, peer review, and international AI conferences.
Selected Publications
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Liang, S., Jiao, T., Du, W., & Qu, S. (2021). An improved ant colony optimization algorithm based on context for tourism route planning. PLoS One, 16(9), e0257317. (Cited by 66)
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Liang, S., Zhu, B., Zhang, Y., Cheng, S., & Jin, J. (2020). A double channel CNN-LSTM model for text classification. IEEE International Conference on High Performance Computing and Communications. (Cited by 32)
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Li, X., Zhang, Y., Jin, J., Sun, F., Li, N., & Liang, S. (2023). A model of integrating convolution and BiGRU dual-channel mechanism for Chinese medical text classifications. PLoS One, 18(3), e0282824. (Cited by 19)
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Liang, S., Chen, X., Ma, J., Du, W., & Ma, H. (2021). An improved double channel long short‐term memory model for medical text classification. Journal of Healthcare Engineering, 2021(1), 6664893. (Cited by 13)
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Liang, S., Jin, J., Ren, J., Du, W., & Qu, S. (2023). An improved dual-channel deep Q-network model for tourism recommendation. Big Data, 11(4), 268–281. (Cited by 9)
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Qu, S., Zhou, H., Zhang, B., & Liang, S. (2022). MSPNet: Multi-scale strip pooling network for road extraction from remote sensing images. Applied Sciences, 12(8), 4068. (Cited by 9)
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Cui, Y., Liang, S., & Zhang, Y. Y. (2024). Multimodal representation learning for tourism recommendation with two-tower architecture. PLoS One, 19(2), e0299370. (Cited by 7)