Lanh Tat Tran
- Statistics and Probability top 0.5%
- Finance top 1%
- Artificial Intelligence top 5%
- Management Science and Operations Research top 2%
- Economics and Econometrics top 5%
- Co-authors
- Tuan D. PhamGeorge G. RoussasMichel CarbonMarc HallinNgai Hang ChanD. IoannidesZudi LuSidney Yakowitz
- Topics
- Statistical Methods and Inference (26 papers)Financial Risk and Volatility Modeling (17 papers)Bayesian Methods and Mixture Models (16 papers)
- Journals
- Journal of the American Statistical AssociationThe Annals of StatisticsProceedings of the American Mathematical Society
- Partner nations
- United StatesFranceChina
In The Last Decade
Lanh Tat Tran
49 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 63
- Statistics and Probability 928
- Finance 503
- Artificial Intelligence 361
- Management Science and Operations Research 336
- Economics and Econometrics 317
Countries citing papers authored by Lanh Tat Tran
This map shows the geographic impact of Lanh Tat Tran'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 Lanh Tat Tran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lanh Tat Tran more than expected).
Fields of papers citing papers by Lanh Tat Tran
This network shows the impact of papers produced by Lanh Tat Tran. 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 Lanh Tat Tran. The network helps show where Lanh Tat Tran may publish in the future.
Co-authorship network of co-authors of Lanh Tat Tran
This figure shows the co-authorship network connecting the top 25 collaborators of Lanh Tat Tran. A scholar is included among the top collaborators of Lanh Tat Tran 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 Lanh Tat Tran. Lanh Tat Tran is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 18 | |
| 3 | 6 | |
| 4 | 55 | |
| 5 | 4 | |
| 6 | 3 | |
| 7 | 17 | |
| 8 | 25 | |
| 9 | 22 | |
| 10 | 129 | |
| 11 | 49 | |
| 12 | 127 | |
| 13 | 21 | |
| 14 | 6 | |
| 15 | 212 | |
| 16 | 2 | |
| 17 | 3 | |
| 18 | 68 | |
| 19 | 9 | |
| 20 | 0 |
About Lanh Tat Tran
Lanh Tat Tran is a scholar working on Statistics and Probability, Finance and Statistics, Probability and Uncertainty, having authored 51 papers that have together received 1.4k indexed citations. Recurring topics across this work include Statistical Methods and Inference (26 papers), Financial Risk and Volatility Modeling (17 papers) and Bayesian Methods and Mixture Models (16 papers). The work is most often cited by research in Statistics and Probability (928 citations), Finance (503 citations) and Management Science and Operations Research (336 citations). Lanh Tat Tran has collaborated with scholars based in United States, France and China. Frequent co-authors include Tuan D. Pham, George G. Roussas, Michel Carbon, Marc Hallin, Ngai Hang Chan, D. Ioannides, Zudi Lu, Sidney Yakowitz, Berlin Wu and Christian Francq. Their work appears in journals such as Journal of the American Statistical Association, The Annals of Statistics and Proceedings of the American Mathematical Society.
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.