Thomas D. Garvey

58 total papers · 1.1k total citations
34 papers, 535 citations indexed

About

Thomas D. Garvey is a scholar working on Artificial Intelligence, Computer Networks and Communications and General Health Professions. According to data from OpenAlex, Thomas D. Garvey has authored 34 papers receiving a total of 535 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 4 papers in Computer Networks and Communications and 3 papers in General Health Professions. Recurrent topics in Thomas D. Garvey's work include AI-based Problem Solving and Planning (5 papers), Bayesian Modeling and Causal Inference (5 papers) and Logic, Reasoning, and Knowledge (4 papers). Thomas D. Garvey is often cited by papers focused on AI-based Problem Solving and Planning (5 papers), Bayesian Modeling and Causal Inference (5 papers) and Logic, Reasoning, and Knowledge (4 papers). Thomas D. Garvey collaborates with scholars based in United States, Australia and Canada. Thomas D. Garvey's co-authors include John D. Lowrance, Martin A. Fischler, Teresa F. Lunt, Michael Cavanagh, Xiaolei Qian, Matthew J. Koster, Jinping Lai, Kenneth J. Warrington, Tao Han and Linda M. Murphy and has published in prestigious journals such as Gastroenterology, IEEE Transactions on Geoscience and Remote Sensing and Mayo Clinic Proceedings.

In The Last Decade

Thomas D. Garvey

31 papers receiving 477 citations

Author Peers

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

Author						Papers	Cites
Thomas D. Garvey	253	97	84	79	73	34	535
Yi Zhou	91 0.4×	42 0.4×	37 0.4×	51 0.6×	49 0.7×	40	480
Michael Monticino	83 0.3×	67 0.7×	70 0.8×	146 1.8×	36 0.5×	26	495
Hoyeop Lee	223 0.9×	81 0.8×	62 0.7×	20 0.3×	57 0.8×	18	492
Fazel Famili	307 1.2×	20 0.2×	104 1.2×	20 0.3×	143 2.0×	23	554
Carlos Bousoño‐Calzón	182 0.7×	74 0.8×	45 0.5×	146 1.8×	19 0.3×	28	459
Xinxin Wang	92 0.4×	83 0.9×	57 0.7×	13 0.2×	73 1.0×	44	535
Meiqing Wang	156 0.6×	24 0.2×	216 2.6×	56 0.7×	19 0.3×	70	533
Martin Bobák	178 0.7×	29 0.3×	72 0.9×	85 1.1×	18 0.2×	20	551
Francisco J. R. Ruiz	261 1.0×	23 0.2×	56 0.7×	50 0.6×	64 0.9×	24	589
You Song	121 0.5×	26 0.3×	80 1.0×	49 0.6×	54 0.7×	36	512

Countries citing papers authored by Thomas D. Garvey

Since Specialization

Citations

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

Fields of papers citing papers by Thomas D. Garvey

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Thomas D. Garvey. 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 Thomas D. Garvey. The network helps show where Thomas D. Garvey may publish in the future.

Co-authorship network of co-authors of Thomas D. Garvey

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas D. Garvey. A scholar is included among the top collaborators of Thomas D. Garvey 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 Thomas D. Garvey. Thomas D. Garvey 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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