Donna L. Hudson

90 total papers · 1.5k total citations
48 papers, 713 citations indexed

About

Donna L. Hudson is a scholar working on Artificial Intelligence, Information Systems and Signal Processing. According to data from OpenAlex, Donna L. Hudson has authored 48 papers receiving a total of 713 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 9 papers in Information Systems and 7 papers in Signal Processing. Recurrent topics in Donna L. Hudson's work include Artificial Intelligence and Decision Support Systems (9 papers), Time Series Analysis and Forecasting (7 papers) and Neural Networks and Applications (6 papers). Donna L. Hudson is often cited by papers focused on Artificial Intelligence and Decision Support Systems (9 papers), Time Series Analysis and Forecasting (7 papers) and Neural Networks and Applications (6 papers). Donna L. Hudson collaborates with scholars based in United States and United Kingdom. Donna L. Hudson's co-authors include Maurice E. Cohen, Peter B. Raven, Michael L. Smith, Richard L. Lammers, Birgit Jensen, John A. Lucas, A. O. Latunde‐Dada, Fen‐Lei Chang, Mark Kramer and Andrew J. Szeri and has published in prestigious journals such as Journal of the American College of Cardiology, IEEE Transactions on Pattern Analysis and Machine Intelligence and Medicine & Science in Sports & Exercise.

In The Last Decade

Donna L. Hudson

43 papers receiving 673 citations

Author Peers

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

Author Last Decade Papers Cites
Donna L. Hudson 240 147 138 107 95 48 713
Gangmin Ning 200 0.8× 22 0.1× 192 1.4× 31 0.3× 30 0.3× 62 718
Bo von Schéele 150 0.6× 68 0.5× 145 1.1× 15 0.1× 26 0.3× 21 648
Ling Guan 121 0.5× 35 0.2× 63 0.5× 27 0.3× 42 0.4× 59 645
Hisakazu Ogura 198 0.8× 41 0.3× 92 0.7× 78 0.7× 19 0.2× 87 810
Alexander Franz 72 0.3× 106 0.7× 95 0.7× 153 1.4× 41 0.4× 57 624
Aftab Ali 56 0.2× 20 0.1× 66 0.5× 34 0.3× 145 1.5× 59 820
Ke Yu 55 0.2× 98 0.7× 163 1.2× 8 0.1× 61 0.6× 91 816
Yongqiang Lyu 62 0.3× 19 0.1× 232 1.7× 19 0.2× 139 1.5× 66 868
Myung-Jin Choi 68 0.3× 53 0.4× 68 0.5× 142 1.3× 11 0.1× 40 893
Hariton Costin 241 1.0× 28 0.2× 105 0.8× 35 0.3× 69 0.7× 114 859

Countries citing papers authored by Donna L. Hudson

Since Specialization
Citations

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

Fields of papers citing papers by Donna L. Hudson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Donna L. Hudson. 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 Donna L. Hudson. The network helps show where Donna L. Hudson may publish in the future.

Co-authorship network of co-authors of Donna L. Hudson

This figure shows the co-authorship network connecting the top 25 collaborators of Donna L. Hudson. A scholar is included among the top collaborators of Donna L. Hudson 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 Donna L. Hudson. Donna L. Hudson 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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