This map shows the geographic impact of Guang Dai's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Guang Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guang Dai more than expected).
This network shows the impact of papers produced by Guang Dai. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Guang Dai. The network helps show where Guang Dai may publish in the future.
Co-authorship network of co-authors of Guang Dai
This figure shows the co-authorship network connecting the top 25 collaborators of Guang Dai.
A scholar is included among the top collaborators of Guang Dai based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Guang Dai. Guang Dai is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Zhang, Zhihua, Guang Dai, & Michael I. Jordan. (2010). Matrix-Variate Dirichlet Process Mixture Models. International Conference on Artificial Intelligence and Statistics. 980–987.6 indexed citations
Zhang, Zhihua, Guang Dai, Donghui Wang, & Michael I. Jordan. (2010). Bayesian Generalized Kernel Models. International Conference on Artificial Intelligence and Statistics. 972–979.6 indexed citations
14.
Zhang, Zhihua & Guang Dai. (2009). Optimal Scoring for Unsupervised Learning. Neural Information Processing Systems. 22. 2241–2249.3 indexed citations
15.
Dai, Guang & Dit‐Yan Yeung. (2007). Boosting kernel discriminant analysis and its application to tissue classification of gene expression data. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 744–749.5 indexed citations
16.
Yeung, Dit‐Yan, Hong Chang, & Guang Dai. (2007). A scalable kernel-based algorithm for semi-supervised metric learning. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 1138–1143.5 indexed citations
17.
Dai, Guang & Dit–Yan Yeung. (2006). Tensor embedding methods. National Conference on Artificial Intelligence. 1(1). 330–335.66 indexed citations
18.
Dai, Guang & Yuntao Qian. (2004). Face recognition using novel LDA-based algorithms. European Conference on Artificial Intelligence. 455–459.
19.
Dai, Guang, et al.. (2003). Feature Extraction Method Based on the Generalized Weighted Foley-Sammon Transform in High Dimensional Spaces.. Indian International Conference on Artificial Intelligence. 578–589.1 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.