Juanjuan Fan

1.2k total citations
52 papers, 822 citations indexed

About

Juanjuan Fan is a scholar working on Statistics and Probability, Artificial Intelligence and Economics and Econometrics. According to data from OpenAlex, Juanjuan Fan has authored 52 papers receiving a total of 822 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Statistics and Probability, 11 papers in Artificial Intelligence and 7 papers in Economics and Econometrics. Recurrent topics in Juanjuan Fan's work include Statistical Methods and Inference (18 papers), Statistical Methods and Bayesian Inference (12 papers) and Glaucoma and retinal disorders (6 papers). Juanjuan Fan is often cited by papers focused on Statistical Methods and Inference (18 papers), Statistical Methods and Bayesian Inference (12 papers) and Glaucoma and retinal disorders (6 papers). Juanjuan Fan collaborates with scholars based in United States, Germany and Canada. Juanjuan Fan's co-authors include Richard A. Levine, Xiaogang Su, Martha E. Nunn, Li Hsu, Chris A. Johnson, Kimberly E. Cello, Peter Calhoun, Michael A. Kass, Guy Cafri and Tingting Ge and has published in prestigious journals such as Journal of the American Statistical Association, Biometrics and Ophthalmology.

In The Last Decade

Juanjuan Fan

49 papers receiving 781 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Juanjuan Fan United States 19 219 141 129 125 69 52 822
Ting Ye China 17 119 0.5× 93 0.7× 39 0.3× 82 0.7× 72 1.0× 95 776
K. D. Zamba United States 13 155 0.7× 157 1.1× 36 0.3× 91 0.7× 83 1.2× 29 717
Marianne Frisén Sweden 18 278 1.3× 41 0.3× 97 0.8× 38 0.3× 193 2.8× 47 907
Alessandro Santaniello Italy 18 33 0.2× 75 0.5× 111 0.9× 90 0.7× 126 1.8× 29 1.2k
Irene Epifanio Spain 18 122 0.6× 35 0.2× 175 1.4× 15 0.1× 12 0.2× 62 775
Laura Freeman United States 14 133 0.6× 29 0.2× 85 0.7× 14 0.1× 28 0.4× 59 880
Philipp Probst Germany 10 27 0.1× 7 0.0× 177 1.4× 57 0.5× 88 1.3× 17 878
Mark Werner United States 16 170 0.8× 27 0.2× 120 0.9× 21 0.2× 225 3.3× 36 795
Alan J. Gross United States 18 399 1.8× 8 0.1× 116 0.9× 55 0.4× 114 1.7× 67 1.6k
Bikas K. Sinha India 13 376 1.7× 9 0.1× 63 0.5× 27 0.2× 23 0.3× 96 1.1k

Countries citing papers authored by Juanjuan Fan

Since Specialization
Citations

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

Fields of papers citing papers by Juanjuan Fan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Juanjuan Fan

This figure shows the co-authorship network connecting the top 25 collaborators of Juanjuan Fan. A scholar is included among the top collaborators of Juanjuan Fan 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 Juanjuan Fan. Juanjuan Fan 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.
Fan, Juanjuan, et al.. (2024). Forecasting the direction of the Fed's monetary policy decisions using random forest. Journal of Forecasting. 43(7). 2848–2859. 1 indexed citations
2.
Fan, Juanjuan, et al.. (2023). Assessing Predictive Ability of Dynamic Time Warping Functional Connectivity for ASD Classification. International Journal of Biomedical Imaging. 2023. 1–13. 3 indexed citations
3.
Levine, Richard A., et al.. (2022). Estimating a Dose-Response Relationship in Quasi-Experimental Student Success Studies. International Journal of Artificial Intelligence in Education. 33(1). 155–184. 2 indexed citations
4.
Cafri, Guy, Stephen E. Graves, Art Sedrakyan, et al.. (2019). Postmarket surveillance of arthroplasty device components using machine learning methods. Pharmacoepidemiology and Drug Safety. 28(11). 1440–1447. 8 indexed citations
5.
Cafri, Guy, Peter Calhoun, & Juanjuan Fan. (2019). High dimensional variable selection with clustered data: an application of random multivariate survival forests for detection of outlier medical device components. Journal of Statistical Computation and Simulation. 89(8). 1410–1422. 2 indexed citations
6.
Jahedi, Afrooz, et al.. (2017). Distributed Intrinsic Functional Connectivity Patterns Predict Diagnostic Status in Large Autism Cohort. Brain Connectivity. 7(8). 515–525. 26 indexed citations
7.
Spoon, Kelly M., et al.. (2017). Ensemble Learning for Estimating Individualized Treatment Effects in Student Success Studies. International Journal of Artificial Intelligence in Education. 28(3). 315–335. 34 indexed citations
8.
Spoon, Kelly M., et al.. (2016). Random Forests for Evaluating Pedagogy and Informing Personalized Learning. Zenodo (CERN European Organization for Nuclear Research). 8(2). 20–50. 10 indexed citations
9.
Zhao, Peng, Xiaogang Su, Tingting Ge, & Juanjuan Fan. (2015). Propensity score and proximity matching using random forest. Contemporary Clinical Trials. 47. 85–92. 44 indexed citations
10.
Sharpsten, Lucie, Juanjuan Fan, Shaban Demirel, et al.. (2014). Predicting progressive glaucomatous optic neuropathy using random forests based on longitudinally collected standard automated perimetry data. Investigative Ophthalmology & Visual Science. 55(13). 5619–5619. 1 indexed citations
11.
Maybauer, Marc O., Dirk M. Maybauer, Perenlei Enkhbaatar, et al.. (2014). The Selective Vasopressin Type 1a Receptor Agonist Selepressin (FE 202158) Blocks Vascular Leak in Ovine Severe Sepsis*. Critical Care Medicine. 42(7). e525–e533. 51 indexed citations
12.
Su, Xiaogang, et al.. (2012). Multiple-Inflation Poisson Model with L1 Regularization. Statistica Sinica. 9 indexed citations
13.
Keltner, John L., Chris A. Johnson, Kimberly E. Cello, et al.. (2007). Visual Field Quality Control in the Ocular Hypertension Treatment Study (OHTS). Journal of Glaucoma. 16(8). 665–669. 36 indexed citations
14.
Fan, Juanjuan & Richard A. Levine. (2007). To Amnio or Not To Amnio: That Is the Decision for Bayes. CHANCE. 20(3). 26–32. 1 indexed citations
15.
Keltner, John, Chris A. Johnson, Richard A. Levine, et al.. (2006). The Association between Glaucomatous Visual Fields and Optic Nerve Head Features in the Ocular Hypertension Treatment Study. Ophthalmology. 113(9). 1603–1612. 94 indexed citations
16.
Su, Xiao, et al.. (2004). On Simulating Multivariate Failure Times. International Journal of Applied Mathematics & Statistics. 5. 8–18. 4 indexed citations
17.
Levine, Richard A. & Juanjuan Fan. (2004). An automated (Markov chain) Monte Carlo EM algorithm. Journal of Statistical Computation and Simulation. 74(5). 349–360. 26 indexed citations
18.
Keltner, John L., Chris A. Johnson, Juanjuan Fan, et al.. (2003). Classification of Glaucomatous Visual Field Abnormalities In the Ocular Hypertension Treatment Study (OHTS). Investigative Ophthalmology & Visual Science. 44(13). 75–75. 1 indexed citations
19.
Fan, Juanjuan & Ross L. Prentice. (2002). Covariate-adjusted dependence estimation on a finite bivariate failure time region. Statistica Sinica. 12(3). 689–705. 6 indexed citations
20.
Fan, Juanjuan, Li Hsu, & R. L. Prentice. (2000). Dependence Estimation Over a Finite Bivariate Failure Time Region. Lifetime Data Analysis. 6(4). 343–355. 32 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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