Michael D. Dodd

3.6k citations
89 papers · 2.9k · h-index 23

Impact in

Papers in

Michael D. Dodd

86 papers receiving 2.8k citations

Peers

Michael D. Dodd
Comparison fields: 5 of 90
  • Radiological and Ultrasound Technology 541
  • Cognitive Neuroscience 1.2k
  • Statistics and Probability 456
  • Experimental and Cognitive Psychology 386
  • Human-Computer Interaction 158
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Countries citing papers authored by Michael D. Dodd

Since Specialization
Citations

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

Fields of papers citing papers by Michael D. Dodd

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Michael D. Dodd, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Michael D. Dodd Line = papers co-authored together Michael D. Dodd links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 89 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003566
2 2003306
3 2018175
4 2017168
5 2012147
6 2011131
7 2017121
8 200890
9 201380
10 201980
11 200967
12 201653
13 200648
14 201041
15 200335
16 201635
17 201232
18 200629
19 200428
20 201328

About Michael D. Dodd

Michael D. Dodd is a scholar working on Cognitive Neuroscience, Radiological and Ultrasound Technology, Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology and Human-Computer Interaction, having authored 89 papers that have together received 2.9k indexed citations. Recurring topics across this work include Visual perception and processing mechanisms (36 papers), Visual Attention and Saliency Detection (17 papers), Occupational Health and Safety Research (15 papers), Neural and Behavioral Psychology Studies (10 papers), Face Recognition and Perception (8 papers), Social and Intergroup Psychology (7 papers), Memory Processes and Influences (6 papers) and Evolutionary Psychology and Human Behavior (6 papers). The work is most often cited by research in Radiological and Ultrasound Technology (541 citations), Cognitive Neuroscience (1.2k citations), Statistics and Probability (456 citations), Experimental and Cognitive Psychology (386 citations) and Human-Computer Interaction (158 citations). Michael D. Dodd has collaborated with scholars based in United States, Canada and Netherlands. Frequent co-authors include Behzad Esmaeili, Sogand Hasanzadeh, Jay Pratt, Alan D. Castel, Martin H. Fischer, Colin M. MacLeod, Stefan Van der Stigchel, Erin D. Sheard, Daryl E. Wilson and Uri Bibi. Their work appears in journals such as Journal of Vision, Attention Perception & Psychophysics, Psychological Research, Journal of Construction Engineering and Management and Journal of Experimental Psychology Human Perception & Performance.

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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