The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Yuefeng Li sits on this spectrum.
This scientist: 299 publications — 74th percentile
74% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 991 publications or more.
The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Yuefeng Li sits on this spectrum.
This scientist: 41 D-Index — 40th percentile
40% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 131 D-Index or more.
Yuefeng Li is affiliated with the Queensland University of Technology in Australia. Their research output spans primarily within the field of computer science, focusing notably on artificial intelligence. This work is reflected through a substantial number of publications, with a particular concentration on advanced computational techniques and complex network analysis.
The scientist's research portfolio includes 135 publications in computer science, with subfields covering artificial intelligence, statistical and nonlinear physics, information systems, computer vision and pattern recognition, as well as radiology, nuclear medicine, and imaging.
Key topics addressed in Yuefeng Li's work include:
Recent research papers authored or coauthored by Yuefeng Li provide insight into their current focus areas. Significant publications include:
Their frequent publication venues demonstrate contributions across diverse but specialized outlets in computing and artificial intelligence. These include:
Yuefeng Li collaborates regularly with a range of coauthors, indicating active participation in interdisciplinary and multi-author research projects. Notable frequent coauthors are:
The combined expertise and collaborative efforts contribute to advancements in methodologies such as graph neural networks, machine learning applications in healthcare, and community detection in complex networks. The research spans both theoretical and applied aspects of artificial intelligence within computer science, addressing current challenges in data analysis and network modeling.
Ning Zhong;Yuefeng Li;Sheng-Tang Wu
Raymond Y. K. Lau;S. Y. Liao;Ron Chi-Wai Kwok;Kaiquan Xu
Xujuan Zhou;Yue Xu;Yuefeng Li;Audun Josang
Yuefeng Li;Ning Zhong
R.Y.K. Lau;Dawei Song;Yuefeng Li;T.C.H. Cheung
Xiaohui Tao;Yuefeng Li;Ning Zhong
Sheng-tang Wu;Yuefeng Li;Yue Xu
Sheng-Tang Wu;Yuefeng Li;Yue Xu;Binh Pham
Wanzhong Yang;Yuefeng Li;Yue Xu
Y. Li;C. Zhang;J. R. Swan
Yuefeng Li;Ning Zhong
Huizhi Liang;Yue Xu;Yuefeng Li;Richi Nayak
Yuefeng Li;Abdulmohsen Algarni;Ning Zhong
Yuefeng Li;Abdulmohsen Algarni;Mubarak Albathan;Yan Shen
Kamal Berahmand;Elahe Nasiri;Rojiar Pir mohammadiani;Yuefeng Li
Elahe Nasiri;Kamal Berahmand;Yuefeng Li
Yuefeng Li;Libiao Zhang;Yue Xu;Yiyu Yao
Yang Gao;Yue Xu;Yuefeng Li
Xiaohui Tao;Yuefeng Li;Ning Zhong;Richi Nayak
C.L. Lai;K.Q. Xu;Raymond Y.K. Lau;Y. Li
Yuefeng Li;Abdulmohsen Algarni;Mubarak Albthan;Yan Shen
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