Reva Schwartz

29 total papers · 708 total citations
16 papers, 125 citations indexed

About

Reva Schwartz is a scholar working on Artificial Intelligence, Signal Processing and Industrial and Manufacturing Engineering. According to data from OpenAlex, Reva Schwartz has authored 16 papers receiving a total of 125 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 7 papers in Signal Processing and 2 papers in Industrial and Manufacturing Engineering. Recurrent topics in Reva Schwartz's work include Speech Recognition and Synthesis (8 papers), Speech and Audio Processing (5 papers) and Natural Language Processing Techniques (5 papers). Reva Schwartz is often cited by papers focused on Speech Recognition and Synthesis (8 papers), Speech and Audio Processing (5 papers) and Natural Language Processing Techniques (5 papers). Reva Schwartz collaborates with scholars based in United States, Australia and United Kingdom. Reva Schwartz's co-authors include Harry Hollien, Wade Shen, Joseph P. Campbell, Barbara Rawlins, Christopher Cieri, D. Straub, Nancy F. Chen, William M. Campbell, Fred Richardson and Dominique Estival and has published in prestigious journals such as The Journal of the Acoustical Society of America, Journal of Forensic Sciences and Language Resources and Evaluation.

In The Last Decade

Reva Schwartz

15 papers receiving 112 citations

Author Peers

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

Author						Papers	Cites
Reva Schwartz	73	52	29	12	11	16	125
Andrew Senior	66 0.9×	48 0.9×	16 0.6×		13 1.2×	12	101
Brij Mohan Lal Srivastava	145 2.0×	92 1.8×	8 0.3×		18 1.6×	13	165
Guanlong Zhao	222 3.0×	109 2.1×	86 3.0×		34 3.1×	17	254
Sinem Sonsaat	134 1.8×	56 1.1×	102 3.5×		16 1.5×	10	228
Sudhamay Maity	188 2.6×	174 3.3×	55 1.9×		4 0.4×	10	230
Andrea Vanzo	167 2.3×	31 0.6×	9 0.3×	3 0.3×		15	248
Julian Chan	202 2.8×	119 2.3×	17 0.6×		2 0.2×	11	233
Hannes Pirker	54 0.7×	15 0.3×	30 1.0×		2 0.2×	17	73
Markus Müller	193 2.6×	88 1.7×	18 0.6×		2 0.2×	32	216
Maitreya Patel	102 1.4×	80 1.5×	20 0.7×		48 4.4×	17	129

Countries citing papers authored by Reva Schwartz

Since Specialization

Citations

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

Fields of papers citing papers by Reva Schwartz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Reva Schwartz

This figure shows the co-authorship network connecting the top 25 collaborators of Reva Schwartz. A scholar is included among the top collaborators of Reva Schwartz 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 Reva Schwartz. Reva Schwartz 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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