T. Todd Elvins
- Computer Vision and Pattern Recognition top 5%
- Computer Graphics and Computer-Aided Design top 1%
- Computational Mechanics top 10%
- Human-Computer Interaction top 5%
- Automotive Engineering top 10%
- Co-authors
- Thomas R. NelsonDavid R. NadeauDavid KirshRamesh JainRina SchulStephen J. YoungDavid MartínezJ. Helly
- Topics
- Computer Graphics and Visualization Techniques (9 papers)Augmented Reality Applications (6 papers)Data Visualization and Analytics (6 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignHuman-Computer InteractionComputer Vision and Pattern Recognition
- Journals
- Communications of the ACMFuture Generation Computer SystemsIEEE Computer Graphics and Applications
- Partner nations
- United States
In The Last Decade
T. Todd Elvins
26 papers receiving 473 citations
Peers
Comparison fields: 5 of 88
- Computer Vision and Pattern Recognition 296
- Computer Graphics and Computer-Aided Design 214
- Computational Mechanics 118
- Human-Computer Interaction 97
- Automotive Engineering 69
Countries citing papers authored by T. Todd Elvins
This map shows the geographic impact of T. Todd Elvins'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 T. Todd Elvins with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Todd Elvins more than expected).
Fields of papers citing papers by T. Todd Elvins
This network shows the impact of papers produced by T. Todd Elvins. 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 T. Todd Elvins. The network helps show where T. Todd Elvins may publish in the future.
Co-authorship network of co-authors of T. Todd Elvins
This figure shows the co-authorship network connecting the top 25 collaborators of T. Todd Elvins. A scholar is included among the top collaborators of T. Todd Elvins 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 T. Todd Elvins. T. Todd Elvins is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 22 | |
| 3 | 28 | |
| 4 | 13 | |
| 5 | 1 | |
| 6 | 15 | |
| 7 | 1 | |
| 8 | 18 | |
| 9 | 62 | |
| 10 | 4 | |
| 11 | 22 | |
| 12 | 13 | |
| 13 | Scientific visualization of fluid flow | 2 |
| 14 | 96 | |
| 15 | 16 | |
| 16 | 1 | |
| 17 | 147 | |
| 18 | 17 | |
| 19 | 12 | |
| 20 | 6 |
About T. Todd Elvins
T. Todd Elvins is a scholar working on Computer Graphics and Computer-Aided Design, Human-Computer Interaction and Information Systems and Management, having authored 26 papers that have together received 534 indexed citations. Recurring topics across this work include Computer Graphics and Visualization Techniques (9 papers), Augmented Reality Applications (6 papers) and Data Visualization and Analytics (6 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (214 citations), Human-Computer Interaction (97 citations) and Computer Vision and Pattern Recognition (296 citations). T. Todd Elvins has collaborated with scholars based in United States. Frequent co-authors include Thomas R. Nelson, David R. Nadeau, David Kirsh, Ramesh Jain, Rina Schul, Stephen J. Young, David Martínez, J. Helly, Mark H. Ellisman and Kevin Fall. Their work appears in journals such as Communications of the ACM, Future Generation Computer Systems and IEEE Computer Graphics and Applications.
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.