David A. Sprecher
- Artificial Intelligence top 5%
- Control and Systems Engineering top 10%
- Computational Theory and Mathematics top 5%
- Statistical and Nonlinear Physics top 10%
- Electrical and Electronic Engineering
- Co-authors
- Sorin DrăghiciВладик КрейновичHung T. Nguyen
- Topics
- Neural Networks and Applications (7 papers)Numerical Methods and Algorithms (4 papers)Control Systems and Identification (3 papers)
- Cited by
- Artificial IntelligenceComputational Theory and MathematicsStatistical and Nonlinear Physics
- Journals
- Neural NetworksJournal of Mathematical Analysis and ApplicationsTransactions of the American Mathematical Society
- Partner nations
- United States
In The Last Decade
David A. Sprecher
23 papers receiving 492 citations
Peers
Comparison fields: 5 of 80
- Artificial Intelligence 263
- Control and Systems Engineering 113
- Computational Theory and Mathematics 112
- Statistical and Nonlinear Physics 78
- Electrical and Electronic Engineering 59
Countries citing papers authored by David A. Sprecher
This map shows the geographic impact of David A. Sprecher'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 A. Sprecher with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David A. Sprecher more than expected).
Fields of papers citing papers by David A. Sprecher
This network shows the impact of papers produced by David A. Sprecher. 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 A. Sprecher. The network helps show where David A. Sprecher may publish in the future.
Co-authorship network of co-authors of David A. Sprecher
This figure shows the co-authorship network connecting the top 25 collaborators of David A. Sprecher. A scholar is included among the top collaborators of David A. Sprecher 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 A. Sprecher. David A. Sprecher is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 3 | |
| 3 | 30 | |
| 4 | 55 | |
| 5 | 40 | |
| 6 | 41 | |
| 7 | 39 | |
| 8 | 10 | |
| 9 | 3 | |
| 10 | 4 | |
| 11 | 3 | |
| 12 | 2 | |
| 13 | 4 | |
| 14 | 2 | |
| 15 | 0 | |
| 16 | 9 | |
| 17 | 17 | |
| 18 | 23 | |
| 19 | 19 | |
| 20 | 157 |
About David A. Sprecher
David A. Sprecher is a scholar working on Geometry and Topology, Mathematical Physics and Computational Theory and Mathematics, having authored 24 papers that have together received 550 indexed citations. Recurring topics across this work include Neural Networks and Applications (7 papers), Numerical Methods and Algorithms (4 papers) and Control Systems and Identification (3 papers). The work is most often cited by research in Artificial Intelligence (263 citations), Computational Theory and Mathematics (112 citations) and Statistical and Nonlinear Physics (78 citations). David A. Sprecher has collaborated with scholars based in United States. Frequent co-authors include Sorin Drăghici, Владик Крейнович and Hung T. Nguyen. Their work appears in journals such as Neural Networks, Journal of Mathematical Analysis and Applications and Transactions of the American Mathematical Society.
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.