Joel B. Predd

18 papers receiving 600 citations

Peers

Joel B. Predd
Comparison fields: 5 of 76
  • General Decision Sciences 36
  • Computer Networks and Communications 326
  • Artificial Intelligence 265
  • History and Philosophy of Science 30
  • Philosophy 64
Replace Gabriele Kern-Isberner with:
Gabriele Kern-Isberner Germany
Jiji Zhang United States
Jürg Kohlas Switzerland
Nicholas V. Findler United States
Kevin Baum United States
Lenhart K. Schubert United States
Hélder Coelho Portugal
Piotr J. Gmytrasiewicz United States
Peter J. B. King United Kingdom
Paul Lu Canada
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Citations per year

Countries citing papers authored by Joel B. Predd

Since Specialization
Citations

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

Fields of papers citing papers by Joel B. Predd

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joel B. Predd. 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 Joel B. Predd. The network helps show where Joel B. Predd may publish in the future.

Co-authors

The 25 scholars most cited alongside Joel B. Predd, 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 Joel B. Predd Line = papers co-authored together Joel B. Predd links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006247
2 2009103
3 200989
4 201054
5 200852
6 200847
7 200520
8
Measuring the Effectiveness of Border Security Between Ports-of-Entry
201016
9 20157
10 20176
11
Lessons Learned from the Afghan Mission Network: Developing a Coalition Contingency Network
20145
12 20124
13 20204
14 20063
15 20043
16 20193
17 20212
18
Australia's Naval Shipbuilding Enterprise
20152
19 20201
20 20111

About Joel B. Predd

Joel B. Predd is a scholar working on Computer Networks and Communications, Political Science and International Relations, Ocean Engineering, Artificial Intelligence and Management Science and Operations Research, having authored 21 papers that have together received 670 indexed citations. Recurring topics across this work include Distributed Sensor Networks and Detection Algorithms (6 papers), Decision-Making and Behavioral Economics (2 papers), Forecasting Techniques and Applications (2 papers), Neural Networks and Applications (2 papers), Marine and Offshore Engineering Studies (2 papers), Maritime Ports and Logistics (2 papers), Multi-Criteria Decision Making (2 papers) and Technology Assessment and Management (2 papers). The work is most often cited by research in General Decision Sciences (36 citations), Computer Networks and Communications (326 citations), Artificial Intelligence (265 citations), History and Philosophy of Science (30 citations) and Philosophy (64 citations). Joel B. Predd has collaborated with scholars based in United States. Frequent co-authors include H. Vincent Poor, Sanjeev Kulkarni, Sanjeev R. Kulkarni, Daniel N. Osherson, Shari Lawrence Pfleeger, Jeffrey Hunker, Elliott H. Lieb, Robert Seiringer, Henry H. Willis and Paul K Davis. Their work appears in journals such as IEEE Transactions on Information Theory, IEEE Security & Privacy, IEEE Signal Processing Magazine, Viruses and IEEE Transactions on Information Forensics and Security.

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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