Peter Kugel

565 total citations
29 papers, 322 citations indexed

About

Peter Kugel is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Peter Kugel has authored 29 papers receiving a total of 322 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Computational Theory and Mathematics, 12 papers in Artificial Intelligence and 5 papers in Cognitive Neuroscience. Recurrent topics in Peter Kugel's work include Computability, Logic, AI Algorithms (12 papers), Machine Learning and Algorithms (6 papers) and Algorithms and Data Compression (4 papers). Peter Kugel is often cited by papers focused on Computability, Logic, AI Algorithms (12 papers), Machine Learning and Algorithms (6 papers) and Algorithms and Data Compression (4 papers). Peter Kugel collaborates with scholars based in United States, Germany and Türkiye. Peter Kugel's co-authors include Jan C. Aurich, Benjamin Kirsch, D. M. MACKAY, Stephen Wilson, Allen Kent and Anne Meuwese and has published in prestigious journals such as Communications of the ACM, MIS Quarterly and Cognition.

In The Last Decade

Peter Kugel

24 papers receiving 274 citations

Peers

Peter Kugel
Wallace Feurzeig United States
Marco Elio Tabacchi Italy
Cynthia Solomon United States
Jože Rugelj Slovenia
Jonas Boustedt Sweden
Mandaar B. Pande India
Yen‐Teh Hsia Taiwan
Robert W. Lawler United States
Zalman Usiskin United States
Adrienne Decker United States
Wallace Feurzeig United States
Peter Kugel
Citations per year, relative to Peter Kugel Peter Kugel (= 1×) peers Wallace Feurzeig

Countries citing papers authored by Peter Kugel

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Peter Kugel

This figure shows the co-authorship network connecting the top 25 collaborators of Peter Kugel. A scholar is included among the top collaborators of Peter Kugel 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 Peter Kugel. Peter Kugel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kugel, Peter & Anne Meuwese. (2010). Uncertain Risks Regulated, edited by Michelle Everson and Ellen Vos. Oxford/New York: Routledge-Cavendish, 2009, 456 pp., £90.00, hardcover.. European Journal of Risk Regulation. 1(1). 95–96. 1 indexed citations
2.
Kugel, Peter. (2005). It's time to think outside the computational box. Communications of the ACM. 48(11). 32–37. 12 indexed citations
3.
Kugel, Peter. (2004). Toward a theory of intelligence. Theoretical Computer Science. 317(1-3). 13–30. 5 indexed citations
4.
Kugel, Peter. (2003). Toward a theory of intelligence. Theoretical Computer Science. 317(1-3). 13–30. 5 indexed citations
5.
Kugel, Peter. (1993). How professors develop as teachers. Studies in Higher Education. 18(3). 315–328. 143 indexed citations
6.
Kugel, Peter. (1992). Beyond computational musicology. MIT Press eBooks. 30–48.
7.
Kugel, Peter. (1989). Improving Learning Without Improving Teaching. Computer Science Education. 1(2). 145–152. 8 indexed citations
8.
Kugel, Peter. (1988). How Long Will Computers Stay “Dumb”?. MIS Quarterly. 12(1). 1–3. 3 indexed citations
9.
Wilson, Stephen & Peter Kugel. (1982). Artificial Intelligence and Visual Art. Leonardo. 15(1). 87–87. 2 indexed citations
10.
Kugel, Peter & D. M. MACKAY. (1982). Brains, Machines and Persons. Leonardo. 15(3). 240–240. 7 indexed citations
11.
Kugel, Peter. (1981). Artificial Intelligence and Visual Art. Leonardo. 14(2). 137–137. 3 indexed citations
12.
Kugel, Peter, et al.. (1978). Catalog information and text as indicators of relevance. Journal of the American Society for Information Science. 29(1). 15–30. 24 indexed citations
13.
Kugel, Peter. (1977). Induction, pure and simple. Information and Control. 35(4). 276–336. 24 indexed citations
14.
Kugel, Peter. (1976). What can a computer learn from examples?. ACM SIGART Bulletin. 13–15. 1 indexed citations
15.
Kugel, Peter. (1976). Digital to analog conversion. ACM SIGACT News. 8(2). 27–33. 1 indexed citations
16.
Kugel, Peter. (1975). How to make abstract ideas more concrete. ACM SIGCSE Bulletin. 7(1). 191–195. 1 indexed citations
17.
Kugel, Peter. (1975). A theorem about automatic programming. ACM SIGART Bulletin. 5–8. 6 indexed citations
18.
Kugel, Peter. (1975). How to make abstract ideas more concrete. 191–195. 2 indexed citations
19.
Kugel, Peter. (1971). Dirty Boole?. Journal of the American Society for Information Science. 22(4). 293–294. 1 indexed citations
20.
Kugel, Peter & Allen Kent. (1962). Information retrieval II. 110–110. 1 indexed citations

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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