Tiefeng Ma
Impact in
- Statistics and Probability top 5%
- Statistical Distribution Estimation and Applications
- Advanced Statistical Methods and Models
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
Papers in
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- Advanced Statistical Methods and Models 13
- Statistical Methods and Inference 12
- Statistical Distribution Estimation and Applications 9
- Statistical Methods and Bayesian Inference 5
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- Advanced Clustering Algorithms Research 6
- Bayesian Methods and Mixture Models 5
- Co-authors
- Shuangzhe Liu (26 shared papers)Song-Gui Wang (5 shared papers)Víctor Leiva (3 shared papers)Lin Ma (4 shared papers)Milind Sathye (1 shared paper)Fei Xia (1 shared paper)Yi Zhang (2 shared papers)Haiyun Liu (1 shared paper)
In The Last Decade
Tiefeng Ma
46 papers receiving 285 citations
Peers
Comparison fields: 5 of 69
- Statistics and Probability 131
- Statistics, Probability and Uncertainty 26
- Finance 37
- Artificial Intelligence 100
- Management Science and Operations Research 37
Countries citing papers authored by Tiefeng Ma
This map shows the geographic impact of Tiefeng Ma'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 Tiefeng Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tiefeng Ma more than expected).
Fields of papers citing papers by Tiefeng Ma
This network shows the impact of papers produced by Tiefeng Ma. 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 Tiefeng Ma. The network helps show where Tiefeng Ma may publish in the future.
Co-authors
The 25 scholars most cited alongside Tiefeng Ma, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 40 | |
| 2 | 2019 | 23 | |
| 3 | 2019 | 20 | |
| 4 | 2021 | 16 | |
| 5 | 2023 | 15 | |
| 6 | 2022 | 15 | |
| 7 | 2021 | 15 | |
| 8 | 2015 | 12 | |
| 9 | 2010 | 10 | |
| 10 | 2016 | 10 | |
| 11 | 2018 | 9 | |
| 12 | 2011 | 7 | |
| 13 | 2017 | 6 | |
| 14 | 2020 | 6 | |
| 15 | 2019 | 6 | |
| 16 | 2020 | 6 | |
| 17 | 2009 | 5 | |
| 18 | 2012 | 5 | |
| 19 | 2020 | 5 | |
| 20 | 2014 | 5 |
About Tiefeng Ma
Tiefeng Ma is a scholar working on Statistics and Probability, Artificial Intelligence, Computer Vision and Pattern Recognition, Finance and Signal Processing, having authored 50 papers that have together received 291 indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (13 papers), Statistical Methods and Inference (12 papers), Statistical Distribution Estimation and Applications (9 papers), Advanced Clustering Algorithms Research (6 papers), Financial Markets and Investment Strategies (5 papers), Bayesian Methods and Mixture Models (5 papers), Statistical Methods and Bayesian Inference (5 papers) and Financial Risk and Volatility Modeling (5 papers). The work is most often cited by research in Statistics and Probability (131 citations), Statistics, Probability and Uncertainty (26 citations), Finance (37 citations), Artificial Intelligence (100 citations) and Management Science and Operations Research (37 citations). Tiefeng Ma has collaborated with scholars based in China, Australia and Chile. Frequent co-authors include Shuangzhe Liu, Song-Gui Wang, Víctor Leiva, Lin Ma, Milind Sathye, Fei Xia, Yi Zhang, Haiyun Liu, Chang Tang and Youbo Liu. Their work appears in journals such as Neurocomputing, Statistical Papers, Journal of Statistical Planning and Inference, Information Sciences and Journal of Multivariate Analysis.
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.