Karl Gregory

511 total citations
10 papers, 336 citations indexed

About

Karl Gregory is a scholar working on Statistics and Probability, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Karl Gregory has authored 10 papers receiving a total of 336 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Statistics and Probability, 2 papers in Molecular Biology and 2 papers in Artificial Intelligence. Recurrent topics in Karl Gregory's work include Statistical Methods and Inference (4 papers), Statistical Methods and Bayesian Inference (3 papers) and Bayesian Methods and Mixture Models (2 papers). Karl Gregory is often cited by papers focused on Statistical Methods and Inference (4 papers), Statistical Methods and Bayesian Inference (3 papers) and Bayesian Methods and Mixture Models (2 papers). Karl Gregory collaborates with scholars based in United States, United Kingdom and Iran. Karl Gregory's co-authors include Jim Hamill, Soumendra N. Lahiri, Veerabhadran Baladandayuthapani, Raymond J. Carroll, Daniel J. Nordman, Ehsan Mohammadi, Mike Thelwall, Debraj Das, Kevin R. Coombes and Christopher S. McMahan and has published in prestigious journals such as Journal of the American Statistical Association, Biometrics and The Annals of Statistics.

In The Last Decade

Karl Gregory

10 papers receiving 307 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Karl Gregory United States	7	118	98	71	66	45	10	336
Maher Kachour France	11	21 0.2×	90 0.9×	98 1.4×	38 0.6×	38 0.8×	27	342
Chiang‐nan Chao United States	8	141 1.2×	34 0.3×	5 0.1×	26 0.4×	32 0.7×	25	366
Miguel Godinho de Matos Portugal	11	73 0.6×	177 1.8×	7 0.1×	48 0.7×	152 3.4×	23	375
Li-Chiu Chi Taiwan	9	59 0.5×	43 0.4×	17 0.2×	11 0.2×	11 0.2×	21	343
Marilyn Greenstein United States	8	75 0.6×	39 0.4×	4 0.1×	63 1.0×	14 0.3×	11	434
Chao Min China	12	45 0.4×	88 0.9×	4 0.1×	64 1.0×	32 0.7×	21	395
Jaime Gil-Lafuente Spain	9	46 0.4×	94 1.0×	6 0.1×	48 0.7×	112 2.5×	42	353
Jim Sterne United States	10	45 0.4×	226 2.3×	5 0.1×	121 1.8×	126 2.8×	15	433
Gary P. Schneider United States	9	41 0.3×	38 0.4×	8 0.1×	38 0.6×	20 0.4×	47	368
James K. Loebbecke United States	8	59 0.5×	23 0.2×	62 0.9×	49 0.7×	6 0.1×	15	582

Countries citing papers authored by Karl Gregory

Since Specialization

Citations

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

Fields of papers citing papers by Karl Gregory

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Karl Gregory

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

All Works

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10 of 10 papers shown

1.

Mohammadi, Ehsan, et al.. (2020). Which health and biomedical topics generate the most Facebook interest and the strongest citation relationships?. Information Processing & Management. 57(3). 102230–102230. 21 indexed citations

2.

Das, Debraj, Karl Gregory, & Soumendra N. Lahiri. (2019). Perturbation bootstrap in adaptive Lasso. The Annals of Statistics. 47(4). 11 indexed citations

3.

Gregory, Karl, Soumendra N. Lahiri, & Daniel J. Nordman. (2018). A smooth block bootstrap for quantile regression with time series. The Annals of Statistics. 46(3). 17 indexed citations

4.

Gregory, Karl, et al.. (2018). Adaptive Elastic Net for Group Testing. Biometrics. 75(1). 13–23. 6 indexed citations

5.

Gregory, Karl, Soumendra N. Lahiri, & Daniel J. Nordman. (2015). A Smooth Block Bootstrap for Statistical Functionals and Time Series. Journal of Time Series Analysis. 36(3). 442–461. 4 indexed citations

6.

Gregory, Karl, Raymond J. Carroll, Veerabhadran Baladandayuthapani, & Soumendra N. Lahiri. (2014). A Two-Sample Test for Equality of Means in High Dimension. Journal of the American Statistical Association. 110(510). 837–849. 59 indexed citations

7.

Gregory, Karl, Amin A. Momin, Kevin R. Coombes, & Veerabhadran Baladandayuthapani. (2014). Latent Feature Decompositions for Integrative Analysis of Multi-Platform Genomic Data. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 11(6). 984–994. 6 indexed citations

8.

Gregory, Karl, Kevin R. Coombes, Amin A. Momin, et al.. (2012). Latent feature decompositions for integrative analysis of diverse high-throughput genomic data. 3. 130–134. 4 indexed citations

9.

Gregory, Karl, et al.. (2004). DISFLUENT SPEECH AND THE VISUAL WORLD: AN APPLICATION OF THE VISUAL WORLD PARADIGM TO THE STUDY OF SPOKEN LANGUAGE COMPREHENSION By. 2 indexed citations

10.

Hamill, Jim & Karl Gregory. (1997). Internet marketing in the internationalisation of UK SMEs. Journal of Marketing Management. 13(1-3). 9–28. 206 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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