David Eppstein
Impact in
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- Computational Geometry and Mesh Generation
- Computer Graphics and Visualization Techniques
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- Advanced Graph Theory Research
- Complexity and Algorithms in Graphs
- Graph Labeling and Dimension Problems
Papers in
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- Computational Geometry and Mesh Generation 3
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- Intelligent Tutoring Systems and Adaptive Learning 1
- Algorithms and Data Compression 1
- Co-authors
- Jeff Erickson (1 shared paper)Xiangen Hu (1 shared paper)Jean‐Claude Falmagne (2 shared papers)Dietrich Albert (2 shared papers)Xinyun Hu (1 shared paper)
- Journals
- Discrete & Computational Geometry (2 papers)Algorithmica (1 paper)CERN Document Server (European Organization for Nuclear Research) (1 paper)
- Partner nations
- United StatesChile
In The Last Decade
David Eppstein
5 papers receiving 283 citations
Peers
Comparison fields: 5 of 48
- Computer Graphics and Computer-Aided Design 103
- Computational Theory and Mathematics 147
- Discrete Mathematics and Combinatorics 26
- Computer Science Applications 25
- Architecture 6
Countries citing papers authored by David Eppstein
This map shows the geographic impact of David Eppstein'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 Eppstein with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Eppstein more than expected).
Fields of papers citing papers by David Eppstein
This network shows the impact of papers produced by David Eppstein. 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 Eppstein. The network helps show where David Eppstein may publish in the future.
Co-authors
The 5 scholars most cited alongside David Eppstein, 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 | 2000 | 132 | |
| 2 | 1999 | 107 | |
| 3 | 2013 | 63 | |
| 4 | 1998 | 13 | |
| 5 | Knowledge Space: Application in Education | 2013 | 1 |
About David Eppstein
David Eppstein is a scholar working on Computer Graphics and Computer-Aided Design, Artificial Intelligence, Computational Theory and Mathematics, Signal Processing and Computer Science Applications, having authored 5 papers that have together received 316 indexed citations. Recurring topics across this work include Computational Geometry and Mesh Generation (3 papers), Advanced Graph Theory Research (2 papers), Data Management and Algorithms (1 paper), Intelligent Tutoring Systems and Adaptive Learning (1 paper), Innovative Teaching and Learning Methods (1 paper), Complexity and Algorithms in Graphs (1 paper), Algorithms and Data Compression (1 paper) and E-Learning and Knowledge Management (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (103 citations), Computational Theory and Mathematics (147 citations), Discrete Mathematics and Combinatorics (26 citations), Computer Science Applications (25 citations) and Architecture (6 citations). David Eppstein has collaborated with scholars based in United States and Chile. Frequent co-authors include Jeff Erickson, Xiangen Hu, Jean‐Claude Falmagne, Dietrich Albert and Xinyun Hu. Their work appears in journals such as Discrete & Computational Geometry, Algorithmica and CERN Document Server (European Organization for Nuclear 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.