Todd Mummert

655 citations
13 papers · 466 · h-index 10

Impact in

Papers in

Todd Mummert

13 papers receiving 415 citations

Peers

Todd Mummert
Comparison fields: 5 of 35
  • Hardware and Architecture 114
  • Computer Networks and Communications 331
  • Information Systems 209
  • Signal Processing 47
  • Computer Vision and Pattern Recognition 79
Replace Charles D. Cranor with:
Charles D. Cranor United States
Eunsam Kim South Korea
Anirban Chakrabarti India
William R. Marczak United States
Daniel Ellard United States
Rajat Mukherjee United States
K. Sjoerd Mullender Netherlands
Fabrice Huet France
Mark Day United States
Olivier Zendra France
Todd Mummert relative to Charles D. Cranor United States Charles D. Cranor's profile →
Citations per field
00.5×3.2×
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Citations per year

Countries citing papers authored by Todd Mummert

Since Specialization
Citations

This map shows the geographic impact of Todd Mummert'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 Mummert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Todd Mummert more than expected).

Fields of papers citing papers by Todd Mummert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Todd Mummert. 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 Mummert. The network helps show where Todd Mummert may publish in the future.

Co-authors

The 25 scholars most cited alongside Todd Mummert, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Todd Mummert Line = papers co-authored together Todd Mummert links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 1998173
2 200867
3 198956
4 200334
5 200533
6 201428
7 201123
8 202015
9 199411
10 199610
11 20147
12 20226
13 20023

About Todd Mummert

Todd Mummert is a scholar working on Computer Networks and Communications, Information Systems, Artificial Intelligence, Information Systems and Management and Hardware and Architecture, having authored 13 papers that have together received 466 indexed citations. Recurring topics across this work include Cloud Computing and Resource Management (6 papers), Advanced Data Storage Technologies (4 papers), Software System Performance and Reliability (3 papers), Interconnection Networks and Systems (3 papers), Scientific Computing and Data Management (3 papers), Parallel Computing and Optimization Techniques (2 papers), Machine Learning and Data Classification (2 papers) and Distributed and Parallel Computing Systems (2 papers). The work is most often cited by research in Hardware and Architecture (114 citations), Computer Networks and Communications (331 citations), Information Systems (209 citations), Signal Processing (47 citations) and Computer Vision and Pattern Recognition (79 citations). Todd Mummert has collaborated with scholars based in United States, Brazil and Canada. Frequent co-authors include Pravin Bhagwat, R.O. LaMaire, Richard Han, Vasanth Bala, Bowen Alpern, Glenn Ammons, H. T. Kung, Paul Scherer, Harry Printz and Canturk Isci. Their work appears in journals such as Empirical Software Engineering, ACM SIGMETRICS Performance Evaluation Review, Lecture notes in computer science, IEEE International Conference on Cloud Computing Technology and Science and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.

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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