Chee Yap

5.8k citations
145 papers · 3.1k · h-index 31

Impact in

Papers in

Chee Yap

135 papers receiving 2.8k citations

Peers

Chee Yap
Comparison fields: 5 of 113
  • Computer Graphics and Computer-Aided Design 1.4k
  • Computer Vision and Pattern Recognition 1.3k
  • Computational Theory and Mathematics 829
  • Signal Processing 488
  • Computational Mechanics 598
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F. P. Preparata United States
Sariel Har-Peled United States
Steven Fortune United States
Mark H. Overmars Netherlands
Timothy M. Chan Canada
Jacob E. Goodman United States
Emo Welzl Switzerland
Boris Aronov United States
Allen Van Gelder United States
Otfried Schwarzkopf Netherlands
Chee Yap relative to F. P. Preparata United States F. P. Preparata's profile →
Citations per field
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F. P. Preparata · 1×
Citations per year

Countries citing papers authored by Chee Yap

Since Specialization
Citations

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

Fields of papers citing papers by Chee Yap

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chee Yap. 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 Chee Yap. The network helps show where Chee Yap may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 145 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1985282
2 1987199
3 1988140
4 1983135
5
Fundamental Problems of Algorithmic Algebra
1999129
6 1983106
7 198798
8 198787
9 198484
10 201873
11 200671
12 199067
13 201263
14 199963
15 198553
16 198452
17 199051
18 198649
19 201446
20 198645

About Chee Yap

Chee Yap is a scholar working on Computer Graphics and Computer-Aided Design, Computational Theory and Mathematics, Computer Vision and Pattern Recognition, Computational Mechanics and Industrial and Manufacturing Engineering, having authored 145 papers that have together received 3.1k indexed citations. Recurring topics across this work include Computational Geometry and Mesh Generation (65 papers), Advanced Numerical Analysis Techniques (32 papers), Polynomial and algebraic computation (26 papers), Robotic Path Planning Algorithms (20 papers), Data Management and Algorithms (15 papers), Numerical Methods and Algorithms (13 papers), Optimization and Packing Problems (10 papers) and Digital Image Processing Techniques (10 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (1.4k citations), Computer Vision and Pattern Recognition (1.3k citations), Computational Theory and Mathematics (829 citations), Signal Processing (488 citations) and Computational Mechanics (598 citations). Chee Yap has collaborated with scholars based in United States, Germany and Canada. Frequent co-authors include Colm Ó'Dúnlaing, Richard Cole, Micha Sharir, Alok Aggarwal, Richard Hull, Bernard Chazelle, Hoon Hong, Ee‐Chien Chang, David Kirkpatrick and Gert Vegter. Their work appears in journals such as Algorithmica, Discrete & Computational Geometry, Computational Geometry, Journal of Algorithms and Computer Graphics Forum.

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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