Junni L. Zhang
- Statistics and Probability top 1%
- Economics and Econometrics top 10%
- Artificial Intelligence
- Management Science and Operations Research top 10%
- Finance top 10%
- Co-authors
- Donald B. RubinJun S. LiuWolfgang Karl HärdleFabrizia MealliJohn BryantFan LiRong ChenMing Lin
- Topics
- Statistical Methods and Bayesian Inference (3 papers)demographic modeling and climate adaptation (3 papers)Insurance, Mortality, Demography, Risk Management (3 papers)
- Journals
- The Journal of Chemical PhysicsSHILAP Revista de lepidopterologíaJournal of the American Statistical Association
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Junni L. Zhang
14 papers receiving 514 citations
Peers
Comparison fields: 5 of 109
- Statistics and Probability 292
- Economics and Econometrics 140
- Artificial Intelligence 79
- Management Science and Operations Research 53
- Finance 44
Countries citing papers authored by Junni L. Zhang
This map shows the geographic impact of Junni L. Zhang'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 Junni L. Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junni L. Zhang more than expected).
Fields of papers citing papers by Junni L. Zhang
This network shows the impact of papers produced by Junni L. Zhang. 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 Junni L. Zhang. The network helps show where Junni L. Zhang may publish in the future.
Co-authorship network of co-authors of Junni L. Zhang
This figure shows the co-authorship network connecting the top 25 collaborators of Junni L. Zhang. A scholar is included among the top collaborators of Junni L. Zhang 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 Junni L. Zhang. Junni L. Zhang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Bayesian Text Classification and Summarization via A Class-Specified Topic Model | 13 |
| 2 | 6 | |
| 3 | 30 | |
| 4 | 3 | |
| 5 | 16 | |
| 6 | 3 | |
| 7 | 32 | |
| 8 | 9 | |
| 9 | 17 | |
| 10 | 33 | |
| 11 | 79 | |
| 12 | 24 | |
| 13 | 214 | |
| 14 | 50 |
About Junni L. Zhang
Junni L. Zhang is a scholar working on Statistics and Probability, Management Science and Operations Research and General Social Sciences, having authored 14 papers that have together received 529 indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (3 papers), demographic modeling and climate adaptation (3 papers) and Insurance, Mortality, Demography, Risk Management (3 papers). The work is most often cited by research in Statistics and Probability (292 citations), Economics and Econometrics (140 citations) and Finance (44 citations). Junni L. Zhang has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Donald B. Rubin, Jun S. Liu, Wolfgang Karl Härdle, Fabrizia Mealli, John Bryant, Fan Li, Rong Chen, Ming Lin, Qiansheng Cheng and Feifei Wang. Their work appears in journals such as The Journal of Chemical Physics, SHILAP Revista de lepidopterología and Journal of the American Statistical Association.
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.