Tom McCreedy

49 total papers · 1.1k total citations
40 papers, 882 citations indexed

About

Tom McCreedy is a scholar working on Biomedical Engineering, Electrical and Electronic Engineering and Bioengineering. According to data from OpenAlex, Tom McCreedy has authored 40 papers receiving a total of 882 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Biomedical Engineering, 12 papers in Electrical and Electronic Engineering and 10 papers in Bioengineering. Recurrent topics in Tom McCreedy's work include Microfluidic and Capillary Electrophoresis Applications (19 papers), Electrochemical Analysis and Applications (10 papers) and Analytical Chemistry and Sensors (10 papers). Tom McCreedy is often cited by papers focused on Microfluidic and Capillary Electrophoresis Applications (19 papers), Electrochemical Analysis and Applications (10 papers) and Analytical Chemistry and Sensors (10 papers). Tom McCreedy collaborates with scholars based in United Kingdom, Saudi Arabia and Thailand. Tom McCreedy's co-authors include Gillian M. Greenway, Qi Song, Qijun Song, Stephen J. Haswell, Scott W. Johnson, Victoria Skelton, Jonathan W. Aylott, George N. Doku, Peter R. Fielden and Alan Townshend and has published in prestigious journals such as Chemical Communications, Analytica Chimica Acta and Lab on a Chip.

In The Last Decade

Tom McCreedy

39 papers receiving 855 citations

Author Peers

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

Author						Papers	Cites
Tom McCreedy	578	207	157	155	133	40	882
Willian Toito Suarez	366 0.6×	254 1.2×	121 0.8×	228 1.5×	103 0.8×	63	872
Ekaterina P. Nesterenko	453 0.8×	140 0.7×	364 2.3×	140 0.9×	94 0.7×	44	851
Xing‐Zheng Wu	484 0.8×	162 0.8×	215 1.4×	121 0.8×	134 1.0×	66	846
Takashi Masadome	270 0.5×	214 1.0×	139 0.9×	135 0.9×	150 1.1×	69	714
Sabina Susmel	414 0.7×	236 1.1×	52 0.3×	94 0.6×	167 1.3×	40	738
Ayça Atılır Özcan	209 0.4×	275 1.3×	102 0.6×	208 1.3×	207 1.6×	25	831
Paulo Clairmont Feitosa de Lima Gomes	336 0.6×	124 0.6×	110 0.7×	187 1.2×	52 0.4×	41	809
Leonardo R. Allain	420 0.7×	173 0.8×	98 0.6×	132 0.9×	70 0.5×	27	1.1k
Waleed Alahmad	472 0.8×	266 1.3×	138 0.9×	397 2.6×	227 1.7×	63	937
Agustina Gómez‐Hens	210 0.4×	113 0.5×	191 1.2×	180 1.2×	77 0.6×	53	700

Countries citing papers authored by Tom McCreedy

Since Specialization

Citations

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

Fields of papers citing papers by Tom McCreedy

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tom McCreedy

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