Todd Eavis

488 total citations
24 papers, 207 citations indexed

About

Todd Eavis is a scholar working on Computer Networks and Communications, Signal Processing and Information Systems. According to data from OpenAlex, Todd Eavis has authored 24 papers receiving a total of 207 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Computer Networks and Communications, 22 papers in Signal Processing and 12 papers in Information Systems. Recurrent topics in Todd Eavis's work include Advanced Database Systems and Queries (23 papers), Data Management and Algorithms (22 papers) and Data Mining Algorithms and Applications (8 papers). Todd Eavis is often cited by papers focused on Advanced Database Systems and Queries (23 papers), Data Management and Algorithms (22 papers) and Data Mining Algorithms and Applications (8 papers). Todd Eavis collaborates with scholars based in Canada, United States and Australia. Todd Eavis's co-authors include Andrew Rau‐Chaplin, Frank Dehne, F. Dehne, Ying Chen, Elankayer Sithirasenan, Nasser Taleb, Goetz Graefe, Thomas Neumann, Asadullah Shaikh and Anisoara Nica and has published in prestigious journals such as Future Generation Computer Systems, Distributed and Parallel Databases and Data Science Journal.

In The Last Decade

Todd Eavis

24 papers receiving 196 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Todd Eavis Canada 9 185 143 100 36 22 24 207
Yali Zhu United States 8 219 1.2× 143 1.0× 79 0.8× 68 1.9× 26 1.2× 15 246
Mohamed H. Ali United States 7 167 0.9× 165 1.2× 63 0.6× 75 2.1× 18 0.8× 8 222
Richard Tibbetts United States 3 169 0.9× 94 0.7× 50 0.5× 85 2.4× 14 0.6× 3 184
Ralf Rantzau Germany 6 105 0.6× 86 0.6× 72 0.7× 41 1.1× 21 1.0× 12 159
Jonas Traub Germany 10 215 1.2× 92 0.6× 96 1.0× 127 3.5× 36 1.6× 23 272
Neal Sample United States 4 193 1.0× 173 1.2× 59 0.6× 144 4.0× 21 1.0× 13 226
Leonidas Galanis United States 4 207 1.1× 84 0.6× 95 0.9× 77 2.1× 9 0.4× 7 225
Nabíl Schear United States 8 115 0.6× 93 0.7× 106 1.1× 144 4.0× 9 0.4× 15 210
Sukho Lee South Korea 6 173 0.9× 190 1.3× 85 0.8× 86 2.4× 23 1.0× 16 252
Mohamed Ziauddin United States 4 176 1.0× 136 1.0× 56 0.6× 66 1.8× 14 0.6× 6 185

Countries citing papers authored by Todd Eavis

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Todd Eavis

This figure shows the co-authorship network connecting the top 25 collaborators of Todd Eavis. A scholar is included among the top collaborators of Todd Eavis 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 Todd Eavis. Todd Eavis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Shaikh, Asadullah, et al.. (2015). High performance framework for mining association rules from hierarchical data cubes. International Journal of Business Intelligence and Data Mining. 10(3). 233–233. 2 indexed citations
2.
Eavis, Todd, et al.. (2014). Soft Real-Time OLAP: Exploiting Modern Hardware without Breaking the Bank. 85–94. 1 indexed citations
3.
Graefe, Goetz, et al.. (2013). Elasticity in Cloud Databases and Their Query Processing. International Journal of Data Warehousing and Mining. 9(2). 1–20. 5 indexed citations
4.
Eavis, Todd, et al.. (2013). Minimizing the MOLAP/ROLAP Divide: You Can Have Your Performance and Scale It Too. Journal of Computing Science and Engineering. 7(1). 1–20. 1 indexed citations
5.
Eavis, Todd, et al.. (2012). Query Optimization and Execution in a Parallel Analytics DBMS. 4. 897–908. 4 indexed citations
6.
Chen, Ying, Frank Dehne, Todd Eavis, & Andrew Rau‐Chaplin. (2008). PnP: sequential, external memory, and parallel iceberg cube computation. Distributed and Parallel Databases. 23(2). 99–126. 12 indexed citations
7.
Eavis, Todd, et al.. (2008). Parallel OLAP with the Sidera server. Future Generation Computer Systems. 26(2). 259–266. 11 indexed citations
8.
Dehne, Frank, Todd Eavis, & Andrew Rau‐Chaplin. (2008). RCUBE. International Journal of Data Warehousing and Mining. 4(3). 1–14. 5 indexed citations
9.
Eavis, Todd, et al.. (2007). Rk-hist. 475–484. 12 indexed citations
10.
Eavis, Todd, et al.. (2007). Mapgraph. 465–474. 4 indexed citations
11.
Eavis, Todd, et al.. (2007). The LBF R-tree: Efficient Multidimensional Indexing with Graceful Degradation. 241–250. 3 indexed citations
12.
Chen, Ying, Frank Dehne, Todd Eavis, & Andrew Rau‐Chaplin. (2006). Improved Data Partitioning for Building Large ROLAP Data Cubes in Parallel. International Journal of Data Warehousing and Mining. 2(1). 1–26. 5 indexed citations
13.
Dehne, Frank, Todd Eavis, & Andrew Rau‐Chaplin. (2006). The cgmCUBE project: Optimizing parallel data cube generation for ROLAP. Distributed and Parallel Databases. 19(1). 29–62. 28 indexed citations
14.
Rau‐Chaplin, Andrew, et al.. (2006). cgmOLAP: Efficient Parallel Generation and Querying of Terabyte Size ROLAP Data Cubes. Griffith Research Online (Griffith University, Queensland, Australia). 164–164. 9 indexed citations
15.
Chen, Ying, F. Dehne, Todd Eavis, & Andrew Rau‐Chaplin. (2005). PnP: Parallel and External Memory Iceberg Cube Computation. rj10026. 576–577. 6 indexed citations
16.
Chen, Ying, F. Dehne, Todd Eavis, & Andrew Rau‐Chaplin. (2004). Building large ROLAP data cubes in parallel. 367–377. 11 indexed citations
17.
Dehne, F., Todd Eavis, & Andrew Rau‐Chaplin. (2004). Top-down computation of partial ROLAP data cubes. 11. 10 pp.–10 pp.. 6 indexed citations
18.
Chen, Ying, Frank Dehne, Todd Eavis, & Andrew Rau‐Chaplin. (2004). Parallel ROLAP Data Cube Construction on Shared-Nothing Multiprocessors. Distributed and Parallel Databases. 15(3). 219–236. 33 indexed citations
19.
Rau‐Chaplin, Andrew & Todd Eavis. (2003). Parallel relational olap. 4 indexed citations
20.
Dehne, F., Todd Eavis, & Andrew Rau‐Chaplin. (2003). Parallel multi-dimensional ROLAP indexing. 21 indexed citations

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.

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