Jinchi Lv

46 papers and 4.1k indexed citations i.

About

Jinchi Lv is a scholar working on Statistics and Probability, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Jinchi Lv has authored 46 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Statistics and Probability, 19 papers in Artificial Intelligence and 7 papers in Computational Mechanics. Recurrent topics in Jinchi Lv’s work include Statistical Methods and Inference (31 papers), Bayesian Methods and Mixture Models (9 papers) and Statistical Methods and Bayesian Inference (9 papers). Jinchi Lv is often cited by papers focused on Statistical Methods and Inference (31 papers), Bayesian Methods and Mixture Models (9 papers) and Statistical Methods and Bayesian Inference (9 papers). Jinchi Lv collaborates with scholars based in United States, China and Japan. Jinchi Lv's co-authors include Jianqing Fan, Yingying Fan, Lucas Janson, Emmanuel J. Candès, Qi Lei, Jun S. Liu, Gareth James, Peter Radchenko, Wei Lin and Hiroshi Imamizu and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of the American Statistical Association.

In The Last Decade

Co-authorship network of co-authors of Jinchi Lv i

Fields of papers citing papers by Jinchi Lv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jinchi Lv. 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 Jinchi Lv. The network helps show where Jinchi Lv may publish in the future.

Countries citing papers authored by Jinchi Lv

Since Specialization
Citations

This map shows the geographic impact of Jinchi Lv'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 Jinchi Lv with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jinchi Lv more than expected).

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.

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