David R. Large

1.4k citations
72 papers · 1.0k · h-index 22

Impact in

Papers in

David R. Large

68 papers receiving 989 citations

Peers

David R. Large
Comparison fields: 5 of 88
  • Human-Computer Interaction 263
  • Social Psychology 737
  • Safety, Risk, Reliability and Quality 238
  • Automotive Engineering 226
  • Physical Therapy, Sports Therapy and Rehabilitation 70
Replace Lee Skrypchuk with:
Lee Skrypchuk United Kingdom
Andreas Löcken Germany
Brian Mok United States
Anna-Katharina Frison Germany
Jonathan Dobres United States
David Sirkin United States
Maryam Zahabi United States
Marcel Walch Germany
Nora Broy Germany
Tuomo Kujala Finland
David R. Large relative to Lee Skrypchuk United Kingdom Lee Skrypchuk's profile →
Citations per field
00.5×1.5×
Lee Skrypchuk · 1×
Citations per year

Countries citing papers authored by David R. Large

Since Specialization
Citations

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

Fields of papers citing papers by David R. Large

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David R. Large. 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 David R. Large. The network helps show where David R. Large may publish in the future.

Co-authors

The 25 scholars most cited alongside David R. Large, 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 David R. Large Line = papers co-authored together David R. Large links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 72 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201872
2 201558
3 201954
4 201749
5 202140
6 201637
7 202036
8 201633
9 201432
10 201731
11 201929
12 201929
13 201928
14 201826
15 201326
16 201926
17 201825
18 201623
19 202123
20 201723

About David R. Large

David R. Large is a scholar working on Social Psychology, Safety, Risk, Reliability and Quality, Automotive Engineering, Human-Computer Interaction and Cognitive Neuroscience, having authored 72 papers that have together received 1.0k indexed citations. Recurring topics across this work include Human-Automation Interaction and Safety (53 papers), Traffic and Road Safety (24 papers), Safety Warnings and Signage (17 papers), Spatial Cognition and Navigation (8 papers), Virtual Reality Applications and Impacts (8 papers), Older Adults Driving Studies (7 papers), Tactile and Sensory Interactions (7 papers) and Ergonomics and Musculoskeletal Disorders (7 papers). The work is most often cited by research in Human-Computer Interaction (263 citations), Social Psychology (737 citations), Safety, Risk, Reliability and Quality (238 citations), Automotive Engineering (226 citations) and Physical Therapy, Sports Therapy and Rehabilitation (70 citations). David R. Large has collaborated with scholars based in United Kingdom, United States and India. Frequent co-authors include Gary Burnett, Lee Skrypchuk, Elizabeth Crundall, Orestis Georgiou, Joseph L. Gabbard, A. Bolton, Nagendra R. Velaga, Glyn Lawson, Catherine Harvey and Missie Smith. Their work appears in journals such as Applied Ergonomics, IET Intelligent Transport Systems, Transportation Research Part F Traffic Psychology and Behaviour, Ergonomics and Journal of Safety Research.

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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