Adam Kapelner

3.2k total citations · 1 hit paper
31 papers, 1.9k citations indexed

About

Adam Kapelner is a scholar working on Artificial Intelligence, Statistics and Probability and Management Science and Operations Research. According to data from OpenAlex, Adam Kapelner has authored 31 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 8 papers in Statistics and Probability and 5 papers in Management Science and Operations Research. Recurrent topics in Adam Kapelner's work include Statistical Methods in Clinical Trials (6 papers), Advanced Causal Inference Techniques (5 papers) and Optimal Experimental Design Methods (5 papers). Adam Kapelner is often cited by papers focused on Statistical Methods in Clinical Trials (6 papers), Advanced Causal Inference Techniques (5 papers) and Optimal Experimental Design Methods (5 papers). Adam Kapelner collaborates with scholars based in United States, Israel and Canada. Adam Kapelner's co-authors include Justin Bleich, Emil Pitkin, Alex Goldstein, Dana R. Chandler, Edward I. George, Shane T. Jensen, Peter P. Lee, Susan Holmes, Abba Μ. Krieger and Dana Beth Weinberg and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Biometrics.

In The Last Decade

Adam Kapelner

29 papers receiving 1.9k citations

Hit Papers

Peeking Inside the Black Box: Visualizing Statistical Lea... 2014 2026 2018 2022 2014 250 500 750 1000
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual Conditional Expectation
    2014 1.1k citations Alex Goldstein, Adam Kapelner et al. Journal of Computational and Graphical Statistics profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Adam Kapelner United States 13 524 151 150 133 117 31 1.9k
Bernd Bischl Germany 29 1.9k 3.7× 79 0.5× 153 1.0× 196 1.5× 83 0.7× 112 4.0k
Karl Kumbier United States 6 1.9k 3.6× 107 0.7× 121 0.8× 98 0.7× 61 0.5× 13 3.1k
Yap Bee Wah Malaysia 18 375 0.7× 30 0.2× 273 1.8× 98 0.7× 51 0.4× 81 2.1k
Jan van den Berg Netherlands 22 396 0.8× 68 0.5× 201 1.3× 90 0.7× 22 0.2× 121 3.0k
Eva Cernadas Spain 16 832 1.6× 48 0.3× 55 0.4× 46 0.3× 80 0.7× 59 2.7k
Michael Hahsler United States 19 591 1.1× 45 0.3× 112 0.7× 36 0.3× 24 0.2× 79 2.4k
Terry Sincich United States 18 159 0.3× 36 0.2× 231 1.5× 88 0.7× 145 1.2× 36 2.3k
Allan Tucker United Kingdom 27 577 1.1× 256 1.7× 83 0.6× 59 0.4× 10 0.1× 118 2.5k
Alberto Barbado Spain 3 3.0k 5.6× 115 0.8× 132 0.9× 25 0.2× 85 0.7× 5 5.0k
Weishu Liu China 20 184 0.4× 82 0.5× 242 1.6× 50 0.4× 18 0.2× 44 2.3k

Countries citing papers authored by Adam Kapelner

Since Specialization
Citations

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

Fields of papers citing papers by Adam Kapelner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Adam Kapelner

This figure shows the co-authorship network connecting the top 25 collaborators of Adam Kapelner. A scholar is included among the top collaborators of Adam Kapelner 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 Adam Kapelner. Adam Kapelner 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.
Kapelner, Adam, et al.. (2023). The role of pairwise matching in experimental design for an incidence outcome. Australian & New Zealand Journal of Statistics. 65(4). 379–393.
3.
Benrimoh, David, Toshi A. Furukawa, Charles F. Reynolds, et al.. (2023). Towards Outcome-Driven Patient Subgroups: A Machine Learning Analysis Across Six Depression Treatment Studies. American Journal of Geriatric Psychiatry. 32(3). 280–292. 5 indexed citations
4.
Weinberg, Dana Beth & Adam Kapelner. (2022). Do book consumers discriminate against Black, female, or young authors?. PLoS ONE. 17(6). e0267537–e0267537. 2 indexed citations
5.
Rosenfeld, Ariel, David Benrimoh, Robert Fratila, et al.. (2021). Treatment selection using prototyping in latent-space with application to depression treatment. PLoS ONE. 16(11). e0258400–e0258400. 8 indexed citations
6.
Kapelner, Adam, et al.. (2020). The Bayesian Additive Regression Trees Formula for Safe Machine Learning-Based Intraocular Lens Predictions. Frontiers in Big Data. 3. 572134–572134. 10 indexed citations
7.
Kapelner, Adam, et al.. (2018). Predicting Contextual Informativeness for Vocabulary Learning. IEEE Transactions on Learning Technologies. 11(1). 13–26. 12 indexed citations
8.
Weinberg, Dana Beth & Adam Kapelner. (2018). Comparing gender discrimination and inequality in indie and traditional publishing. PLoS ONE. 13(4). e0195298–e0195298. 15 indexed citations
9.
Kapelner, Adam & Justin Bleich. (2016). bartMachine: Machine Learning with Bayesian Additive Regression Trees. Journal of Statistical Software. 70(4). 160 indexed citations
10.
Schwartz, H. Andrew, Maarten Sap, Margaret L. Kern, et al.. (2015). PREDICTING INDIVIDUAL WELL-BEING THROUGH THE LANGUAGE OF SOCIAL MEDIA. PubMed. 21. 516–527. 95 indexed citations
11.
Kapelner, Adam & Abba Μ. Krieger. (2014). Matching on‐the‐fly: Sequential allocation with higher power and efficiency. Biometrics. 70(2). 378–388. 14 indexed citations
12.
Kapelner, Adam, et al.. (2014). Starvation of cancer via induced ketogenesis and severe hypoglycemia. Medical Hypotheses. 84(3). 162–168. 13 indexed citations
13.
Bleich, Justin, Adam Kapelner, Edward I. George, & Shane T. Jensen. (2014). Variable selection for BART: An application to gene regulation. The Annals of Applied Statistics. 8(3). 84 indexed citations
14.
Goldstein, Alex, Adam Kapelner, Justin Bleich, & Emil Pitkin. (2014). Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual Conditional Expectation. Journal of Computational and Graphical Statistics. 24(1). 44–65. 1105 indexed citations breakdown →
15.
Kapelner, Adam. (2014). Statistical Analysis and Design of Crowdsourcing Applications. ScholarlyCommons (University of Pennsylvania). 1 indexed citations
16.
Kapelner, Adam & Justin Bleich. (2013). bartMachine: A Powerful Tool for Machine Learning.. arXiv (Cornell University). 8 indexed citations
17.
Bleich, Justin, Adam Kapelner, Edward I. George, & Shane T. Jensen. (2013). Variable Selection Inference for Bayesian Additive Regression Trees. arXiv (Cornell University). 3 indexed citations
18.
Chang, Andrew Y., Nupur Bhattacharya, Jian Mu, et al.. (2013). Spatial organization of dendritic cells within tumor draining lymph nodes impacts clinical outcome in breast cancer patients. Journal of Translational Medicine. 11(1). 242–242. 40 indexed citations
19.
Kapelner, Adam, et al.. (2012). New Insights from Coarse Word Sense Disambiguation in the Crowd. International Conference on Computational Linguistics. 539–548. 8 indexed citations
20.
Setiadi, Audi, Holbrook E. Kohrt, Adam Kapelner, et al.. (2010). Quantitative, Architectural Analysis of Immune Cell Subsets in Tumor-Draining Lymph Nodes from Breast Cancer Patients and Healthy Lymph Nodes. PLoS ONE. 5(8). e12420–e12420. 41 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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