Liangyuan Hu

1.7k total citations
57 papers, 1.1k citations indexed

About

Liangyuan Hu is a scholar working on Statistics and Probability, Oncology and Economics and Econometrics. According to data from OpenAlex, Liangyuan Hu has authored 57 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Statistics and Probability, 10 papers in Oncology and 10 papers in Economics and Econometrics. Recurrent topics in Liangyuan Hu's work include Advanced Causal Inference Techniques (17 papers), Statistical Methods and Inference (16 papers) and Health Systems, Economic Evaluations, Quality of Life (8 papers). Liangyuan Hu is often cited by papers focused on Advanced Causal Inference Techniques (17 papers), Statistical Methods and Inference (16 papers) and Health Systems, Economic Evaluations, Quality of Life (8 papers). Liangyuan Hu collaborates with scholars based in United States, Kenya and Canada. Liangyuan Hu's co-authors include Jiayi Ji, Lihua Li, Joseph W. Hogan, Madhu Mazumdar, Bian Liu, Yan Li, Fan Li, Katherine S. Morris, Edward McAuley and Robert W. Motl and has published in prestigious journals such as Nature Communications, Journal of Clinical Oncology and Gastroenterology.

In The Last Decade

Liangyuan Hu

50 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Liangyuan Hu United States 20 225 189 158 158 120 57 1.1k
Sarah L. Hulin-Curtis United Kingdom 13 163 0.7× 76 0.4× 93 0.6× 85 0.5× 171 1.4× 22 941
Benjamin Kasenda Switzerland 25 564 2.5× 84 0.4× 122 0.8× 210 1.3× 208 1.7× 64 1.9k
Shande Chen United States 20 188 0.8× 181 1.0× 216 1.4× 107 0.7× 162 1.4× 47 1.2k
Ikhlaaq Ahmed United Kingdom 13 246 1.1× 78 0.4× 102 0.6× 136 0.9× 70 0.6× 21 991
Anthony J. Hatswell United Kingdom 17 204 0.9× 108 0.6× 54 0.3× 69 0.4× 52 0.4× 65 826
Shijie Ren United Kingdom 19 76 0.3× 63 0.3× 214 1.4× 110 0.7× 69 0.6× 60 983
Ateesha F. Mohamed United States 23 200 0.9× 105 0.6× 85 0.5× 290 1.8× 55 0.5× 66 1.3k
Chun Pang United Kingdom 14 87 0.4× 53 0.3× 107 0.7× 93 0.6× 149 1.2× 33 1.2k
Tea Reljic United States 21 243 1.1× 44 0.2× 49 0.3× 45 0.3× 110 0.9× 91 1.1k
Angelika Geroldinger Austria 15 75 0.3× 72 0.4× 119 0.8× 59 0.4× 76 0.6× 33 848

Countries citing papers authored by Liangyuan Hu

Since Specialization
Citations

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

Fields of papers citing papers by Liangyuan Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Liangyuan Hu

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

All Works

20 of 20 papers shown
1.
2.
Li, Jia, Juan P. Wisnivesky, Adam Gonzalez, et al.. (2024). The association of perceived social support, resilience, and posttraumatic stress symptoms among coronavirus disease patients in the United States. Journal of Affective Disorders. 368. 390–397.
3.
Hu, Liangyuan, et al.. (2023). Historical Redlining, Social Determinants of Health, and Stroke Prevalence in Communities in New York City. JAMA Network Open. 6(4). e235875–e235875. 21 indexed citations
4.
Hu, Liangyuan. (2023). A new method for clustered survival data: Estimation of treatment effect heterogeneity and variable selection. Biometrical Journal. 66(1). e2200178–e2200178. 3 indexed citations
5.
Hu, Liangyuan, Jiayi Ji, Ronald D. Ennis, & Joseph W. Hogan. (2022). A flexible approach for causal inference with multiple treatments and clustered survival outcomes. Statistics in Medicine. 41(25). 4982–4999. 6 indexed citations
6.
Niu, Li, Liangyuan Hu, Yan Li, & Bian Liu. (2022). Correlates of cancer prevalence across census tracts in the United States: A Bayesian machine learning approach. Spatial and Spatio-temporal Epidemiology. 42. 100522–100522.
7.
Hu, Liangyuan, Jiayi Ji, Hao Liu, & Ronald D. Ennis. (2022). A Flexible Approach for Assessing Heterogeneity of Causal Treatment Effects on Patient Survival Using Large Datasets with Clustered Observations. International Journal of Environmental Research and Public Health. 19(22). 14903–14903. 4 indexed citations
8.
Veluswamy, Rajwanth, Liangyuan Hu, Cardinale B. Smith, et al.. (2022). Immunotherapy Outcomes in Individuals With Non–Small Cell Lung Cancer and Poor Performance Status. JNCI Cancer Spectrum. 6(2). 6 indexed citations
9.
Hu, Liangyuan, et al.. (2021). Variable selection with missing data in both covariates and outcomes: Imputation and machine learning. Statistical Methods in Medical Research. 30(12). 2651–2671. 12 indexed citations
10.
Hu, Liangyuan, Jiayi Ji, & Fan Li. (2021). Estimating heterogeneous survival treatment effect in observational data using machine learning. Statistics in Medicine. 40(21). 4691–4713. 41 indexed citations
11.
Hu, Liangyuan & Chenyang Gu. (2021). Estimation of causal effects of multiple treatments in healthcare database studies with rare outcomes. Health Services and Outcomes Research Methodology. 21(3). 287–308. 10 indexed citations
12.
Nayeri, Shadi, Jiayi Ji, Cristian Hernández-Rocha, et al.. (2021). A Role for CXCR3 Ligands as Biomarkers of Post-Operative Crohn’s Disease Recurrence. Journal of Crohn s and Colitis. 16(6). 900–910. 15 indexed citations
13.
Hu, Liangyuan, Jiayi Ji, Yan Li, Bian Liu, & Yiyi Zhang. (2020). Quantile Regression Forests to Identify Determinants of Neighborhood Stroke Prevalence in 500 Cities in the USA: Implications for Neighborhoods with High Prevalence. Journal of Urban Health. 98(2). 259–270. 10 indexed citations
14.
Hu, Liangyuan, Chenyang Gu, Michael J. Lopez, Jiayi Ji, & Juan P. Wisnivesky. (2020). Estimation of causal effects of multiple treatments in observational studies with a binary outcome. Statistical Methods in Medical Research. 29(11). 3218–3234. 43 indexed citations
15.
Hu, Liangyuan, Jiayi Ji, & Fan Li. (2020). Estimating Heterogeneous Survival Treatment Effect via Machine/Deep Learning Methods in Observational Studies. arXiv (Cornell University).
16.
Leng, Siyang, Erin Moshier, Douglas Tremblay, et al.. (2020). Timing of Autologous Stem Cell Transplantation for Multiple Myeloma in the Era of Current Therapies. Clinical Lymphoma Myeloma & Leukemia. 20(10). e734–e751. 2 indexed citations
17.
Ji, Jiayi, Liangyuan Hu, Bian Liu, & Yan Li. (2020). Identifying and assessing the impact of key neighborhood-level determinants on geographic variation in stroke: a machine learning and multilevel modeling approach. BMC Public Health. 20(1). 1666–1666. 9 indexed citations
18.
Ungaro, Ryan C., Liangyuan Hu, Jiayi Ji, et al.. (2020). Machine learning identifies novel blood protein predictors of penetrating and stricturing complications in newly diagnosed paediatric Crohn's disease. Alimentary Pharmacology & Therapeutics. 53(2). 281–290. 32 indexed citations
19.
Hu, Liangyuan & Joseph W. Hogan. (2019). Causal Comparative Effectiveness Analysis of Dynamic Continuous-Time Treatment Initiation Rules With Sparsely Measured Outcomes and Death. Biometrics. 75(2). 695–707. 22 indexed citations
20.
Hu, Liangyuan, Joseph W. Hogan, Ann Mwangi, & Abraham Siika. (2017). Modeling the Causal Effect of Treatment Initiation Time on Survival: Application to HIV/TB Co-infection. Biometrics. 74(2). 703–713. 20 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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