Troy D. Kelley
- Artificial Intelligence top 5%
- Social Psychology top 10%
- Control and Systems Engineering
- Computer Vision and Pattern Recognition top 10%
- Cognitive Neuroscience
- Co-authors
- Lyle N. LongSimon JulierDave BrainesRichard TomsettAlun PreeceFederico CeruttiMurat ŞensoyMoustafa Alzantot
- Topics
- Human-Automation Interaction and Safety (9 papers)Computability, Logic, AI Algorithms (6 papers)Robotics and Automated Systems (5 papers)
- Journals
- SHILAP Revista de lepidopterologíaCognitive ScienceJournal of Vision
- Partner nations
- United StatesUnited KingdomAustralia
In The Last Decade
Troy D. Kelley
35 papers receiving 446 citations
Peers
Comparison fields: 5 of 111
- Artificial Intelligence 230
- Social Psychology 97
- Control and Systems Engineering 60
- Computer Vision and Pattern Recognition 60
- Cognitive Neuroscience 57
Countries citing papers authored by Troy D. Kelley
This map shows the geographic impact of Troy D. Kelley'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 Troy D. Kelley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Troy D. Kelley more than expected).
Fields of papers citing papers by Troy D. Kelley
This network shows the impact of papers produced by Troy D. Kelley. 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 Troy D. Kelley. The network helps show where Troy D. Kelley may publish in the future.
Co-authorship network of co-authors of Troy D. Kelley
This figure shows the co-authorship network connecting the top 25 collaborators of Troy D. Kelley. A scholar is included among the top collaborators of Troy D. Kelley 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 Troy D. Kelley. Troy D. Kelley is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | A Review of Artificial Intelligence (AI) Algorithms for Sound Classification: Implications for Human-Robot Interaction (HRI) | 0 |
| 3 | 3 | |
| 4 | 0 | |
| 5 | 246 | |
| 6 | Computational Cognition Ideation Challenge | 1 |
| 7 | Differences in performance with changing mental workload as the basis for an IMPRINT plug-in proposal | 1 |
| 8 | 3 | |
| 9 | 1 | |
| 10 | 2 | |
| 11 | 10 | |
| 12 | 5 | |
| 13 | 5 | |
| 14 | 6 | |
| 15 | 11 | |
| 16 | 19 | |
| 17 | 1 | |
| 18 | 3 | |
| 19 | Simulating Intelligent Behavior Requires a Complex Approach | 3 |
| 20 | 4 |
About Troy D. Kelley
Troy D. Kelley is a scholar working on Social Psychology, Artificial Intelligence and General Decision Sciences, having authored 38 papers that have together received 488 indexed citations. Recurring topics across this work include Human-Automation Interaction and Safety (9 papers), Computability, Logic, AI Algorithms (6 papers) and Robotics and Automated Systems (5 papers). The work is most often cited by research in Health Informatics (16 citations), Artificial Intelligence (230 citations) and Social Psychology (97 citations). Troy D. Kelley has collaborated with scholars based in United States, United Kingdom and Australia. Frequent co-authors include Lyle N. Long, Simon Julier, Dave Braines, Richard Tomsett, Alun Preece, Federico Cerutti, Murat Şensoy, Moustafa Alzantot, Daniel Harborne and Mani Srivastava. Their work appears in journals such as SHILAP Revista de lepidopterología, Cognitive Science and Journal of Vision.
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.