David S. Prerau
- Artificial Intelligence top 10%
- Information Systems top 10%
- Management Information Systems top 10%
- Management Science and Operations Research top 10%
- Signal Processing
- Co-authors
- Robert E. ReinkeMichael KasslerMark AdlerShreya GoyalL. FrenkelDavid A. RubinW. J. Hannan
- Topics
- Big Data and Business Intelligence (3 papers)Music and Audio Processing (2 papers)Music Technology and Sound Studies (2 papers)
- Journals
- AI MagazinePerspectives of New MusicIEEE Expert
- Partner nations
- United States
In The Last Decade
David S. Prerau
15 papers receiving 244 citations
Peers
Comparison fields: 5 of 67
- Artificial Intelligence 108
- Information Systems 75
- Management Information Systems 48
- Management Science and Operations Research 42
- Signal Processing 40
Countries citing papers authored by David S. Prerau
This map shows the geographic impact of David S. Prerau'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 S. Prerau with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David S. Prerau more than expected).
Fields of papers citing papers by David S. Prerau
This network shows the impact of papers produced by David S. Prerau. 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 S. Prerau. The network helps show where David S. Prerau may publish in the future.
Co-authorship network of co-authors of David S. Prerau
This figure shows the co-authorship network connecting the top 25 collaborators of David S. Prerau. A scholar is included among the top collaborators of David S. Prerau 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 David S. Prerau. David S. Prerau is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Worldwide Intelligent Systems: Approaches to Telecommunications and Network Management | 4 |
| 2 | Verification and validation of expert systems: experience with four diverse systems | 5 |
| 3 | 13 | |
| 4 | Developing and managing expert systems | 48 |
| 5 | Developing and Managing Expert Systems: Proven Techniques for Business and Industry | 33 |
| 6 | 36 | |
| 7 | 9 | |
| 8 | The COMPASS Expert System: Verification, Technology Transfer, and Expansion. | 8 |
| 9 | 92 | |
| 10 | Airport Surface Traffic Control System Requirements Analysis. | 1 |
| 11 | HIGHWAY AIR POLLUTION DISPERSION MODELING: PRELIMINARY EVALUATION OF THIRTEEN MODELS | 3 |
| 12 | 18 | |
| 13 | Year-Round Daylight Saving Time Study : Volume 1. Interim Report on the Operation and Effects of Daylight Saving Time | 2 |
| 14 | 12 | |
| 15 | 13 |
About David S. Prerau
David S. Prerau is a scholar working on Software, Management Information Systems and Music, having authored 15 papers that have together received 297 indexed citations. Recurring topics across this work include Big Data and Business Intelligence (3 papers), Music and Audio Processing (2 papers) and Music Technology and Sound Studies (2 papers). The work is most often cited by research in Software (21 citations), Management Information Systems (48 citations) and Signal Processing (40 citations). David S. Prerau has collaborated with scholars based in United States. Frequent co-authors include Robert E. Reinke, Michael Kassler, Mark Adler, Shreya Goyal, L. Frenkel, David A. Rubin and W. J. Hannan. Their work appears in journals such as AI Magazine, Perspectives of New Music and IEEE Expert.
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.