Dr. Ling Zheng | Computer Science and Artificial Intelligence | Research Excellence Award
Fujian Maternity and Children Health Hospital | China
The researcher holds advanced training in computer science with a strong specialization in artificial intelligence and machine learning, Computer Science and Artificial Intelligence particularly in efficient attention mechanisms and multimodal large models for medical and healthcare applications. Current research focuses on the development of intelligent systems for placental pathology analysis, automated diagnostic report generation, and AI-assisted clinical decision support. Major contributions include the construction of annotated medical image databases, AI-guided lesion standardization frameworks, and the application of dynamic intelligent models to support maternal health interventions. The research portfolio also extends to large-scale data management, privacy protection, and secure data sharing technologies for auditory and visual cognitive models, as well as knowledge graph representation and swarm intelligence collaboration. In addition to academic research, the work includes close collaboration with industry partners to develop domain-specific large models for gynecologic oncology and multimodal AI systems for placental pathology diagnosis. Scholarly contributions span high-impact peer-reviewed journals in artificial intelligence, medical informatics, data science, and interdisciplinary computational research. The researcher has also contributed to the academic community through service on program committees for leading international conferences in artificial intelligence, computer vision, and data analytics. Overall, the research demonstrates strong innovation, translational impact, and commitment to advancing AI-driven healthcare technologies.
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Featured Publications
Computer-aided detection of prostate cancer in T2-weighted MRI within the peripheral zone
A. Rampun, L. Zheng, P. Malcolm, B. Tiddeman, R. Zwiggelaar – Physics in Medicine & Biology, 61(13), 4796, 2016
Self-adjusting harmony search-based feature selection
L. Zheng, R. Diao, Q. Shen – Soft Computing, 19(6), 1567–1579, 2015
Feature grouping and selection: A graph-based approach
L. Zheng, F. Chao, N. Mac Parthaláin, D. Zhang, Q. Shen – Information Sciences, 546, 1256–1272, 2021
Boundary-aware network with two-stage partial decoders for salient object detection in remote sensing images
Q. Zheng, L. Zheng, Y. Bai, H. Liu, J. Deng, Y. Li – IEEE Transactions on Geoscience and Remote Sensing, 61, 1–13, 2023
Progressively real-time video salient object detection via cascaded fully convolutional networks with motion attention
Q. Zheng, Y. Li, L. Zheng, Q. Shen – Neurocomputing, 467, 465–475, 2022
T. Wang, L. Zheng, H. Lv, C. Zhou, Y. Shen, Q. Qiu, Y. Li, P. Li, G. Wang – Expert Systems with Applications, 213, 119216