Kevin D. Wayne

668 citations
30 papers · 427 · h-index 13

Impact in

Papers in

Kevin D. Wayne

28 papers receiving 417 citations

Peers

Kevin D. Wayne
Comparison fields: 5 of 75
  • Urology 50
  • Computational Theory and Mathematics 112
  • Computer Science Applications 30
  • Psychiatry and Mental health 65
  • Computer Networks and Communications 93
Replace Ah Reum Kang with:
Ah Reum Kang South Korea
Lothar Gierl Germany
Karl Trygve Kalleberg Norway
Alireza Fallah United States
Timo Knuutila Finland
Po‐Hsun Cheng Taiwan
Raymond Cheng United States
Tim A. Carnes United States
Alper Çağlayan United States
Emilia Farcas United States
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Citations per field
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Citations per year

Countries citing papers authored by Kevin D. Wayne

Since Specialization
Citations

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

Fields of papers citing papers by Kevin D. Wayne

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kevin D. Wayne. 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 Kevin D. Wayne. The network helps show where Kevin D. Wayne may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200253
2 200247
3 199834
4 201834
5 201632
6 201728
7 201827
8
Introduction to Programming in Python: An Interdisciplinary Approach
200724
9 199923
10 200117
11 201815
12 201914
13
Faster approximation algorithms for generalized flow
199913
14
Computer Science: An Interdisciplinary Approach
201612
15 201812
16 20206
17 20216
18 20125
19 20174
20 20204

About Kevin D. Wayne

Kevin D. Wayne is a scholar working on Computational Theory and Mathematics, Computer Science Applications, Surgery, Computer Graphics and Computer-Aided Design and Software, having authored 30 papers that have together received 427 indexed citations. Recurring topics across this work include Complexity and Algorithms in Graphs (6 papers), Bladder and Urothelial Cancer Treatments (6 papers), Teaching and Learning Programming (3 papers), Advanced Graph Theory Research (3 papers), Spreadsheets and End-User Computing (2 papers), Sports Analytics and Performance (2 papers), Mathematics and Applications (2 papers) and Constraint Satisfaction and Optimization (2 papers). The work is most often cited by research in Urology (50 citations), Computational Theory and Mathematics (112 citations), Computer Science Applications (30 citations), Psychiatry and Mental health (65 citations) and Computer Networks and Communications (93 citations). Kevin D. Wayne has collaborated with scholars based in United States, Canada and Finland. Frequent co-authors include Lisa Fleischer, Robert Sedgewick, Jeffrey C. Loh-Doyle, Éva Tardos, Stuart D. Boyd, Mukul B. Patil, Siamak Daneshmand, Hooman Djaladat, Thomas G. Clifford and Anne K. Schuckman. Their work appears in journals such as Urology, The Journal of Sexual Medicine, The Journal of Urology, SIAM Journal on Discrete Mathematics and Urologic Oncology Seminars and Original Investigations.

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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