Lan Liu
- Statistics and Probability top 5%
- Economics and Econometrics top 10%
- Sociology and Political Science
- Artificial Intelligence
- Finance top 10%
- Co-authors
- Michael G. HudgensXiao‐yuan DongXiaoying ZhengChangqing LuoQing LiuWang MiaoBaoluo SunEric J. Tchetgen Tchetgen
- Topics
- Statistical Methods and Inference (12 papers)Advanced Causal Inference Techniques (10 papers)Statistical Methods and Bayesian Inference (9 papers)
- Partner nations
- United StatesChinaSingapore
In The Last Decade
Lan Liu
36 papers receiving 418 citations
Peers
Comparison fields: 5 of 103
- Statistics and Probability 108
- Economics and Econometrics 102
- Sociology and Political Science 62
- Artificial Intelligence 50
- Finance 47
Countries citing papers authored by Lan Liu
This map shows the geographic impact of Lan Liu'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 Lan Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lan Liu more than expected).
Fields of papers citing papers by Lan Liu
This network shows the impact of papers produced by Lan Liu. 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 Lan Liu. The network helps show where Lan Liu may publish in the future.
Co-authorship network of co-authors of Lan Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Lan Liu. A scholar is included among the top collaborators of Lan Liu 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 Lan Liu. Lan Liu 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 | 6 | |
| 4 | 2 | |
| 5 | 3 | |
| 6 | 7 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 0 | |
| 11 | 4 | |
| 12 | 5 | |
| 13 | 2 | |
| 14 | 9 | |
| 15 | 23 | |
| 16 | On the subway fire risk assessment based on the dynamically variable weight Petri net | 2 |
| 17 | Identification and Inference for Marginal Average Treatment Effect on the Treated With an Instrumental Variable | 6 |
| 18 | 70 | |
| 19 | 1 | |
| 20 | The Discovery of Technology Innovation Opportunity Based on the Text Mining and the Technology Roadmap | 1 |
About Lan Liu
Lan Liu is a scholar working on Statistics and Probability, Finance and Analytical Chemistry, having authored 42 papers that have together received 429 indexed citations. Recurring topics across this work include Statistical Methods and Inference (12 papers), Advanced Causal Inference Techniques (10 papers) and Statistical Methods and Bayesian Inference (9 papers). The work is most often cited by research in Statistics and Probability (108 citations), General Energy (5 citations) and Finance (47 citations). Lan Liu has collaborated with scholars based in United States, China and Singapore. Frequent co-authors include Michael G. Hudgens, Xiao‐yuan Dong, Xiaoying Zheng, Changqing Luo, Qing Liu, Wang Miao, Baoluo Sun, Eric J. Tchetgen Tchetgen, Eric Tchetgen Tchetgen and Chengyan Yue. Their work appears in journals such as Journal of the American Statistical Association, Neurology and Stroke.
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.