Kai‐Tai Fang

78 papers and 1.6k indexed citations i.

About

Kai‐Tai Fang is a scholar working on Management Science and Operations Research, Computational Theory and Mathematics and Industrial and Manufacturing Engineering. According to data from OpenAlex, Kai‐Tai Fang has authored 78 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Management Science and Operations Research, 40 papers in Computational Theory and Mathematics and 28 papers in Industrial and Manufacturing Engineering. Recurrent topics in Kai‐Tai Fang’s work include Optimal Experimental Design Methods (46 papers), Advanced Multi-Objective Optimization Algorithms (36 papers) and Manufacturing Process and Optimization (26 papers). Kai‐Tai Fang is often cited by papers focused on Optimal Experimental Design Methods (46 papers), Advanced Multi-Objective Optimization Algorithms (36 papers) and Manufacturing Process and Optimization (26 papers). Kai‐Tai Fang collaborates with scholars based in China, Hong Kong and United States. Kai‐Tai Fang's co-authors include Peter Winker, Yi‐Zeng Liang, Qing‐Song Xu, Xiaoqun Wang, Chang‐Xing Ma, Jianxin Pan, Hong Qin, Yongdao Zhou, Min‐Qian Liu and Gennian Ge and has published in prestigious journals such as Mathematics of Computation, The Annals of Statistics and Chemometrics and Intelligent Laboratory Systems.

In The Last Decade

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

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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2025