Shulamith T. Gross

38 total papers · 856 total citations
24 papers, 635 citations indexed

About

Shulamith T. Gross is a scholar working on Statistics and Probability, Economics and Econometrics and Artificial Intelligence. According to data from OpenAlex, Shulamith T. Gross has authored 24 papers receiving a total of 635 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Statistics and Probability, 7 papers in Economics and Econometrics and 5 papers in Artificial Intelligence. Recurrent topics in Shulamith T. Gross's work include Statistical Methods and Inference (7 papers), Statistical Methods and Bayesian Inference (7 papers) and Bayesian Methods and Mixture Models (4 papers). Shulamith T. Gross is often cited by papers focused on Statistical Methods and Inference (7 papers), Statistical Methods and Bayesian Inference (7 papers) and Bayesian Methods and Mixture Models (4 papers). Shulamith T. Gross collaborates with scholars based in United States, Australia and Israel. Shulamith T. Gross's co-authors include Martin A. Tanner, Tze Leung Lai, Srilata Zaheer, Lilac Nachum, David Feldman, William Steiger, M. Donbrow, Simon Benita, Amnon Hoffman and Amnon Hoffman and has published in prestigious journals such as Journal of the American Statistical Association, Management Science and Biometrics.

In The Last Decade

Shulamith T. Gross

24 papers receiving 583 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Shulamith T. Gross	216	103	91	89	80	24	635
Jack C. Lee	421 1.9×	5 0.0×	98 1.1×	270 3.0×	42 0.5×	24	702
Naushad Mamode Khan	232 1.1×	94 0.9×	102 1.1×	51 0.6×	38 0.5×	67	566
Anabel Forte	176 0.8×	28 0.3×	163 1.8×	72 0.8×	26 0.3×	40	772
A. S. Paulson	201 0.9×	49 0.5×	131 1.4×	62 0.7×	14 0.2×	26	572
Maximilian Kasy	125 0.6×	21 0.2×	217 2.4×	58 0.7×	47 0.6×	32	588
Kevin McNally	36 0.2×	32 0.3×	41 0.5×	23 0.3×	93 1.2×	57	722
Hans Schneeweiß	275 1.3×	31 0.3×	132 1.5×	92 1.0×	18 0.2×	63	719
Gerald Keller	47 0.2×	157 1.5×	54 0.6×	45 0.5×	74 0.9×	15	693
Friedhelm Eicker	305 1.4×	18 0.2×	125 1.4×	60 0.7×	29 0.4×	23	576
Mark Yuying An	102 0.5×	46 0.4×	285 3.1×	48 0.5×	21 0.3×	27	596

Countries citing papers authored by Shulamith T. Gross

Since Specialization

Citations

This map shows the geographic impact of Shulamith T. Gross'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 Shulamith T. Gross with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shulamith T. Gross more than expected).

Fields of papers citing papers by Shulamith T. Gross

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shulamith T. Gross. 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 Shulamith T. Gross. The network helps show where Shulamith T. Gross may publish in the future.

Co-authorship network of co-authors of Shulamith T. Gross

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

All Works

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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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