Man‐Lai Tang
- Statistics and Probability top 0.2%
- Artificial Intelligence top 5%
- Management Science and Operations Research top 2%
- Statistics, Probability and Uncertainty top 1%
- Sociology and Political Science top 10%
- Co-authors
- Niansheng TangGuo‐Liang TianKai Wang NgHon Keung Tony NgMaozai TianMing TanWai‐Yin PoonPing Shing Chan
- Topics
- Statistical Methods and Bayesian Inference (82 papers)Statistical Methods and Inference (68 papers)Statistical Methods in Clinical Trials (53 papers)
- Cited by
- Statistics and ProbabilityStatistics, Probability and UncertaintyManagement Science and Operations Research
- Partner nations
- Hong KongChinaUnited States
In The Last Decade
Man‐Lai Tang
159 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 165
- Statistics and Probability 1.3k
- Artificial Intelligence 315
- Management Science and Operations Research 229
- Statistics, Probability and Uncertainty 198
- Sociology and Political Science 132
Countries citing papers authored by Man‐Lai Tang
This map shows the geographic impact of Man‐Lai Tang'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 Man‐Lai Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Man‐Lai Tang more than expected).
Fields of papers citing papers by Man‐Lai Tang
This network shows the impact of papers produced by Man‐Lai Tang. 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 Man‐Lai Tang. The network helps show where Man‐Lai Tang may publish in the future.
Co-authorship network of co-authors of Man‐Lai Tang
This figure shows the co-authorship network connecting the top 25 collaborators of Man‐Lai Tang. A scholar is included among the top collaborators of Man‐Lai Tang 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 Man‐Lai Tang. Man‐Lai Tang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 0 | |
| 8 | 9 | |
| 9 | 7 | |
| 10 | 12 | |
| 11 | 82 | |
| 12 | 17 | |
| 13 | 7 | |
| 14 | THE NESTED DIRICHLET DISTRIBUTION AND INCOMPLETE CATEGORICAL DATA ANALYSIS | 5 |
| 15 | 16 | |
| 16 | 30 | |
| 17 | 88 | |
| 18 | 2 | |
| 19 | 8 | |
| 20 | 1 |
About Man‐Lai Tang
Man‐Lai Tang is a scholar working on Statistics and Probability, Management Science and Operations Research and Artificial Intelligence, having authored 173 papers that have together received 1.9k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (82 papers), Statistical Methods and Inference (68 papers) and Statistical Methods in Clinical Trials (53 papers). The work is most often cited by research in Statistics and Probability (1.3k citations), Statistics, Probability and Uncertainty (198 citations) and Management Science and Operations Research (229 citations). Man‐Lai Tang has collaborated with scholars based in Hong Kong, China and United States. Frequent co-authors include Niansheng Tang, Guo‐Liang Tian, Kai Wang Ng, Hon Keung Tony Ng, Maozai Tian, Ming Tan, Wai‐Yin Poon, Ping Shing Chan, William R. Schucany and Jiajuan Liang. Their work appears in journals such as PLoS ONE, Biometrics and IEEE Transactions on Image Processing.
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.