Jiewen Liu

552 total citations
4 papers, 460 citations indexed

About

Jiewen Liu is a scholar working on Statistics and Probability, Artificial Intelligence and Economics and Econometrics. According to data from OpenAlex, Jiewen Liu has authored 4 papers receiving a total of 460 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Statistics and Probability, 1 paper in Artificial Intelligence and 1 paper in Economics and Econometrics. Recurrent topics in Jiewen Liu's work include Statistical Methods and Bayesian Inference (1 paper), Advanced Graph Neural Networks (1 paper) and Advanced Causal Inference Techniques (1 paper). Jiewen Liu is often cited by papers focused on Statistical Methods and Bayesian Inference (1 paper), Advanced Graph Neural Networks (1 paper) and Advanced Causal Inference Techniques (1 paper). Jiewen Liu collaborates with scholars based in Taiwan and United States. Jiewen Liu's co-authors include Eric R. Ziegel, Shein Chung Chow, Shein‐Chung Chow, Eric J. Tchetgen Tchetgen and Bing Chen and has published in prestigious journals such as Technometrics, American Journal of Epidemiology and Computers, materials & continua/Computers, materials & continua (Print).

In The Last Decade

Jiewen Liu

4 papers receiving 392 citations

Peers

Jiewen Liu

SP

MSOR

PPCH

EE

AC

Joakim Nyberg Sweden

Karey Kowalski United States

Kenneth G. Kowalski United States

Naitee Ting United States

R L Lalonde United States

Yann Merlé France

Fairouz Makhlouf United States

P. A. Lockwood United States

Ulrika Wählby Sweden

Sam Haidar United States

Joakim Nyberg Sweden

Jiewen Liu

191 ×0.9

SP

85 ×0.7

MSOR

45 ×0.7

PPCH

37 ×0.7

EE

18 ×0.4

AC

Citations per year, relative to Jiewen Liu Jiewen Liu (= 1×) peers Joakim Nyberg

Countries citing papers authored by Jiewen Liu

Since Specialization

Citations

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

Fields of papers citing papers by Jiewen Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiewen Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Jiewen Liu. A scholar is included among the top collaborators of Jiewen 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 Jiewen Liu. Jiewen Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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4 of 4 papers shown

1.

Liu, Jiewen, et al.. (2024). Regression-based proximal causal inference. American Journal of Epidemiology. 194(7). 2030–2036. 3 indexed citations

2.

Liu, Jiewen, et al.. (2024). PIAFGNN: Property Inference Attacks against Federated Graph Neural Networks. Computers, materials & continua/Computers, materials & continua (Print). 82(2). 1857–1877. 1 indexed citations

3.

Ziegel, Eric R., Shein‐Chung Chow, & Jiewen Liu. (1996). Statistical Design and Analysis in Pharmaceutical Science. Technometrics. 38(1). 90–90. 37 indexed citations

4.

Ziegel, Eric R., Shein Chung Chow, & Jiewen Liu. (1994). Design and Analysis of Bioavailability and Bioequivalence Studies. Technometrics. 36(2). 232–232. 419 indexed citations

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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