Will Usher
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- Computer Graphics and Visualization Techniques 18
- Computational Geometry and Mesh Generation 3
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- Advanced Vision and Imaging 4
- Data Visualization and Analytics 3
- Graph Theory and Algorithms 2
- Biophysics top 10%
- Computational Mechanics top 10%
- 3D Shape Modeling and Analysis 5
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- Advanced Data Storage Technologies 6
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- Data Management and Algorithms 3
- Co-authors
- Valerio PascucciIngo WaldAaron KnollPeer‐Timo BremerFrederick FedererAlessandra AngelucciHank ChildsJames Kress
- Cited by
- Computer Graphics and Computer-Aided DesignComputer Vision and Pattern RecognitionBiophysics
- Journals
- IEEE Transactions on Visualization and Computer Graphics (5 papers)Computer Graphics Forum (2 papers)Computer Physics Communications (1 paper)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Will Usher
22 papers receiving 315 citations
Peers
Comparison fields: 5 of 62
- Computer Graphics and Computer-Aided Design 161
- Computer Vision and Pattern Recognition 147
- Biophysics 24
- Computational Mechanics 75
- Information Systems and Management 25
Countries citing papers authored by Will Usher
This map shows the geographic impact of Will Usher'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 Will Usher with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Will Usher more than expected).
Fields of papers citing papers by Will Usher
This network shows the impact of papers produced by Will Usher. 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 Will Usher. The network helps show where Will Usher may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Will Usher, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2023 | 2 | |
| 4 | 2023 | 1 | |
| 5 | 2022 | 6 | |
| 6 | 2021 | 6 | |
| 7 | 2021 | 17 | |
| 8 | 2020 | 4 | |
| 9 | 2020 | 10 | |
| 10 | 2020 | 18 | |
| 11 | 2020 | 7 | |
| 12 | 2019 | 20 | |
| 13 | 2019 | 6 | |
| 14 | 2019 | 11 | |
| 15 | 2019 | 13 | |
| 16 | 2018 | 13 | |
| 17 | 2017 | 1 | |
| 18 | 2016 | 76 | |
| 19 | 2016 | 1 | |
| 20 | 2015 | 25 |
About Will Usher
Will Usher is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition, Human-Computer Interaction, Biophysics and Computational Mechanics, having authored 25 papers that have together received 323 indexed citations. Recurring topics across this work include Computer Graphics and Visualization Techniques (18 papers), Advanced Data Storage Technologies (6 papers), 3D Shape Modeling and Analysis (5 papers), Advanced Vision and Imaging (4 papers), Computational Geometry and Mesh Generation (3 papers), Data Visualization and Analytics (3 papers), Data Management and Algorithms (3 papers) and Graph Theory and Algorithms (2 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (161 citations), Computer Vision and Pattern Recognition (147 citations), Biophysics (24 citations), Computational Mechanics (75 citations) and Information Systems and Management (25 citations). Will Usher has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Valerio Pascucci, Ingo Wald, Aaron Knoll, Peer‐Timo Bremer, Frederick Federer, Alessandra Angelucci, Hank Childs, James Kress, Berk Geveci and Chris R. Johnson. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Computer Graphics Forum, Computer Physics Communications, IEEE Computer Graphics and Applications and Computing in Science & Engineering.
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.