Peter Kugel
Impact in
- Education top 10%
- Evaluation of Teaching Practices
- Reflective Practices in Education
- Online and Blended Learning
- Teacher Education and Leadership Studies
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- Computability, Logic, AI Algorithms
Papers in
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- Computability, Logic, AI Algorithms 12
- semigroups and automata theory 3
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- Machine Learning and Algorithms 6
- Algorithms and Data Compression 4
- Co-authors
- Jan C. Aurich (1 shared paper)Benjamin Kirsch (1 shared paper)D. M. MACKAY (1 shared paper)Allen Kent (1 shared paper)Stephen Wilson (1 shared paper)Anne Meuwese (1 shared paper)
- Journals
- Leonardo (3 papers)Theoretical Computer Science (2 papers)Communications of the ACM (1 paper)Production Engineering (1 paper)Behavioral and Brain Sciences (1 paper)
- Partner nations
- United StatesGermanyBelgium
In The Last Decade
Peter Kugel
24 papers receiving 277 citations
Peers
Comparison fields: 5 of 81
- Education 128
- Computational Theory and Mathematics 64
- Computer Science Applications 14
- Artificial Intelligence 74
- Library and Information Sciences 3
Countries citing papers authored by Peter Kugel
This map shows the geographic impact of Peter Kugel'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 Peter Kugel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Kugel more than expected).
Fields of papers citing papers by Peter Kugel
This network shows the impact of papers produced by Peter Kugel. 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 Peter Kugel. The network helps show where Peter Kugel may publish in the future.
Co-authors
The 6 scholars most cited alongside Peter Kugel, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1993 | 145 | |
| 2 | 2010 | 26 | |
| 3 | 1977 | 25 | |
| 4 | 1986 | 25 | |
| 5 | 1978 | 24 | |
| 6 | 2005 | 12 | |
| 7 | 2002 | 12 | |
| 8 | 1989 | 8 | |
| 9 | 1982 | 7 | |
| 10 | 1975 | 6 | |
| 11 | 1969 | 6 | |
| 12 | 2003 | 5 | |
| 13 | 2004 | 5 | |
| 14 | 1988 | 3 | |
| 15 | 1981 | 3 | |
| 16 | 1982 | 2 | |
| 17 | 1975 | 2 | |
| 18 | 1990 | 2 | |
| 19 | 1994 | 2 | |
| 20 | 1975 | 1 |
About Peter Kugel
Peter Kugel is a scholar working on Computational Theory and Mathematics, Artificial Intelligence, Cognitive Neuroscience, Information Systems and Computer Vision and Pattern Recognition, having authored 29 papers that have together received 326 indexed citations. Recurring topics across this work include Computability, Logic, AI Algorithms (12 papers), Machine Learning and Algorithms (6 papers), Algorithms and Data Compression (4 papers), semigroups and automata theory (3 papers), Library Science and Information Systems (2 papers), Music Technology and Sound Studies (2 papers), Experimental Learning in Engineering (2 papers) and Teaching and Learning Programming (2 papers). The work is most often cited by research in Education (128 citations), Computational Theory and Mathematics (64 citations), Computer Science Applications (14 citations), Artificial Intelligence (74 citations) and Library and Information Sciences (3 citations). Peter Kugel has collaborated with scholars based in United States, Germany and Belgium. Frequent co-authors include Jan C. Aurich, Benjamin Kirsch, D. M. MACKAY, Allen Kent, Stephen Wilson and Anne Meuwese. Their work appears in journals such as Leonardo, Theoretical Computer Science, Communications of the ACM, Production Engineering and Behavioral and Brain Sciences.
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.