Kai‐Tai Fang

About

Kai‐Tai Fang is a scholar working on Statistics and Probability, Management Science and Operations Research and Computational Theory and Mathematics. According to data from OpenAlex, Kai‐Tai Fang has authored 86 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Statistics and Probability, 19 papers in Management Science and Operations Research and 16 papers in Computational Theory and Mathematics. Recurrent topics in Kai‐Tai Fang’s work include Advanced Statistical Methods and Models (26 papers), Optimal Experimental Design Methods (16 papers) and Statistical Distribution Estimation and Applications (16 papers). Kai‐Tai Fang is often cited by papers focused on Advanced Statistical Methods and Models (26 papers), Optimal Experimental Design Methods (16 papers) and Statistical Distribution Estimation and Applications (16 papers). Kai‐Tai Fang collaborates with scholars based in Hong Kong, China and United States. Kai‐Tai Fang's co-authors include Samuel Kotz, Kai Wang Ng, Runze Li, Agus Sudjianto, Hong‐Bin Fang, Chang‐Xing Ma, Peter Winker, T. W. Anderson, Yi‐Zeng Liang and Ramalingam Shanmugam and has published in prestigious journals such as Journal of the American Statistical Association, Technometrics and Journal of Chromatography A.

In The Last Decade

Co-authorship network of co-authors of Kai‐Tai Fang i

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Fields of papers citing papers by Kai‐Tai Fang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kai‐Tai Fang. 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 Kai‐Tai Fang. The network helps show where Kai‐Tai Fang may publish in the future.

Countries citing papers authored by Kai‐Tai Fang

Since Specialization

Citations

This map shows the geographic impact of Kai‐Tai Fang'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 Kai‐Tai Fang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kai‐Tai Fang more than expected).

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.

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