Tien-Chung Hu
- Management Science and Operations Research top 1%
- Statistics and Probability top 0.5%
- Mathematical Physics top 5%
- Finance top 5%
- Artificial Intelligence top 10%
- Co-authors
- Andrei VolodinRobert L. TaylorYoung K. TruongJianqing FanAndrew RosalskyShuhe HuFerenc MóriczSoo Hak Sung
- Topics
- Probability and Risk Models (49 papers)Stochastic processes and statistical mechanics (21 papers)Financial Risk and Volatility Modeling (11 papers)
- Journals
- Journal of Mathematical Analysis and ApplicationsThe American StatisticianAmerican Mathematical Monthly
- Partner nations
- TaiwanCanadaUnited States
In The Last Decade
Tien-Chung Hu
50 papers receiving 796 citations
Peers
Comparison fields: 5 of 54
- Management Science and Operations Research 634
- Statistics and Probability 483
- Mathematical Physics 291
- Finance 225
- Artificial Intelligence 174
Countries citing papers authored by Tien-Chung Hu
This map shows the geographic impact of Tien-Chung Hu'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 Tien-Chung Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tien-Chung Hu more than expected).
Fields of papers citing papers by Tien-Chung Hu
This network shows the impact of papers produced by Tien-Chung Hu. 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 Tien-Chung Hu. The network helps show where Tien-Chung Hu may publish in the future.
Co-authorship network of co-authors of Tien-Chung Hu
This figure shows the co-authorship network connecting the top 25 collaborators of Tien-Chung Hu. A scholar is included among the top collaborators of Tien-Chung Hu 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 Tien-Chung Hu. Tien-Chung Hu 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 | 0 | |
| 3 | 0 | |
| 4 | 6 | |
| 5 | 0 | |
| 6 | 6 | |
| 7 | 8 | |
| 8 | 7 | |
| 9 | 1 | |
| 10 | 3 | |
| 11 | 17 | |
| 12 | 11 | |
| 13 | 2 | |
| 14 | 1 | |
| 15 | 3 | |
| 16 | 14 | |
| 17 | 0 | |
| 18 | 30 | |
| 19 | Robust Non-parametric Function Estimation | 162 |
| 20 | 3 |
About Tien-Chung Hu
Tien-Chung Hu is a scholar working on Management Science and Operations Research, Mathematical Physics and Statistics and Probability, having authored 61 papers that have together received 875 indexed citations. Recurring topics across this work include Probability and Risk Models (49 papers), Stochastic processes and statistical mechanics (21 papers) and Financial Risk and Volatility Modeling (11 papers). The work is most often cited by research in Statistics and Probability (483 citations), Management Science and Operations Research (634 citations) and Mathematical Physics (291 citations). Tien-Chung Hu has collaborated with scholars based in Taiwan, Canada and United States. Frequent co-authors include Andrei Volodin, Robert L. Taylor, Young K. Truong, Jianqing Fan, Andrew Rosalsky, Shuhe Hu, Ferenc Móricz, Soo Hak Sung, Pingyan Chen and Xuejun Wang. Their work appears in journals such as Journal of Mathematical Analysis and Applications, The American Statistician and American Mathematical Monthly.
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.