Todd Eavis
Impact in
- Signal Processing top 5%
- Data Management and Algorithms
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- Advanced Database Systems and Queries
- Advanced Data Storage Technologies
- Peer-to-Peer Network Technologies
- Distributed and Parallel Computing Systems
Papers in
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- Advanced Database Systems and Queries 23
- Advanced Data Storage Technologies 7
- Peer-to-Peer Network Technologies 2
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- Data Management and Algorithms 22
- Co-authors
- Andrew Rau‐Chaplin (14 shared papers)Frank Dehne (8 shared papers)F. Dehne (6 shared papers)Ying Chen (5 shared papers)Elankayer Sithirasenan (1 shared paper)Ilia Petrov (1 shared paper)Goetz Graefe (1 shared paper)Thomas Neumann (1 shared paper)
- Journals
- International Journal of Data Warehousing and Mining (3 papers)Distributed and Parallel Databases (3 papers)Data Science Journal (1 paper)Future Generation Computer Systems (1 paper)Journal of Computing Science and Engineering (1 paper)
- Partner nations
- CanadaUnited StatesAustralia
In The Last Decade
Todd Eavis
24 papers receiving 196 citations
Peers
Comparison fields: 5 of 26
- Signal Processing 143
- Computer Networks and Communications 185
- Information Systems 100
- Computational Mathematics 1
- Artificial Intelligence 36
Countries citing papers authored by Todd Eavis
This map shows the geographic impact of Todd Eavis'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 Todd Eavis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Todd Eavis more than expected).
Fields of papers citing papers by Todd Eavis
This network shows the impact of papers produced by Todd Eavis. 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 Todd Eavis. The network helps show where Todd Eavis may publish in the future.
Co-authors
The 11 scholars most cited alongside Todd Eavis, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2004 | 33 | |
| 2 | 2006 | 28 | |
| 3 | 2003 | 21 | |
| 4 | 2002 | 16 | |
| 5 | 2007 | 12 | |
| 6 | 2008 | 12 | |
| 7 | 2004 | 11 | |
| 8 | 2008 | 11 | |
| 9 | 2006 | 9 | |
| 10 | 2005 | 6 | |
| 11 | 2004 | 6 | |
| 12 | 2005 | 6 | |
| 13 | 2006 | 5 | |
| 14 | 2013 | 5 | |
| 15 | 2008 | 5 | |
| 16 | Parallel relational olap | 2003 | 4 |
| 17 | 2007 | 4 | |
| 18 | 2012 | 4 | |
| 19 | 2007 | 3 | |
| 20 | 2015 | 2 |
About Todd Eavis
Todd Eavis is a scholar working on Computer Networks and Communications, Signal Processing, Information Systems, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 24 papers that have together received 207 indexed citations. Recurring topics across this work include Advanced Database Systems and Queries (23 papers), Data Management and Algorithms (22 papers), Data Mining Algorithms and Applications (8 papers), Advanced Data Storage Technologies (7 papers), Cloud Computing and Resource Management (3 papers), Peer-to-Peer Network Technologies (2 papers), Semantic Web and Ontologies (2 papers) and Algorithms and Data Compression (2 papers). The work is most often cited by research in Signal Processing (143 citations), Computer Networks and Communications (185 citations), Information Systems (100 citations), Computational Mathematics (1 citation) and Artificial Intelligence (36 citations). Todd Eavis has collaborated with scholars based in Canada, United States and Australia. Frequent co-authors include Andrew Rau‐Chaplin, Frank Dehne, F. Dehne, Ying Chen, Elankayer Sithirasenan, Ilia Petrov, Goetz Graefe, Thomas Neumann, Asadullah Shaikh and Nasser Taleb. Their work appears in journals such as International Journal of Data Warehousing and Mining, Distributed and Parallel Databases, Data Science Journal, Future Generation Computer Systems and Journal of Computing Science and 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.