Peter Cheng

100 papers receiving 1.2k citations

Peers

Peter Cheng
Comparison fields: 5 of 126
  • Human-Computer Interaction 179
  • Experimental and Cognitive Psychology 357
  • Developmental and Educational Psychology 284
  • Computer Science Applications 90
  • Computer Vision and Pattern Recognition 302
Replace Bipin Indurkhya with:
Bipin Indurkhya Poland
Dennis E. Egan United States
Scott Douglass United States
Michal Dziemianko United Kingdom
Michael Matessa United States
Michael E. Atwood United States
Yuichiro Anzai Japan
Daniel Bothell United States
Peter C. R. Lane United Kingdom
Alonso Vera United States
Peter Cheng relative to Bipin Indurkhya Poland Bipin Indurkhya's profile →
Citations per field
00.5×1.7×
Bipin Indurkhya · 1×
Citations per year

Countries citing papers authored by Peter Cheng

Since Specialization
Citations

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

Fields of papers citing papers by Peter Cheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 117 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018130
2 2000106
3 2003103
4 200190
5 199983
6 200266
7 200262
8 200937
9 201031
10 200628
11 200127
12 199825
13 199624
14 199923
15 202322
16 200722
17 200421
18 201718
19 200218
20 200217

About Peter Cheng

Peter Cheng is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology, Developmental and Educational Psychology and Computer Networks and Communications, having authored 117 papers that have together received 1.4k indexed citations. Recurring topics across this work include Data Visualization and Analytics (29 papers), Visual and Cognitive Learning Processes (24 papers), Advanced Text Analysis Techniques (19 papers), Semantic Web and Ontologies (17 papers), AI-based Problem Solving and Planning (16 papers), Constraint Satisfaction and Optimization (15 papers), Innovative Teaching and Learning Methods (12 papers) and Design Education and Practice (8 papers). The work is most often cited by research in Human-Computer Interaction (179 citations), Experimental and Cognitive Psychology (357 citations), Developmental and Educational Psychology (284 citations), Computer Science Applications (90 citations) and Computer Vision and Pattern Recognition (302 citations). Peter Cheng has collaborated with scholars based in United Kingdom, United States and Malaysia. Frequent co-authors include David Peebles, Unaizah Obaidellah, Mike Scaife, Ric Lowe, Volker Haarslev, Michael Anderson, Patrick R. Green, Peter Cowling, Samad Ahmadi and Peter C. R. Lane. Their work appears in journals such as Cognitive Science, International Journal of Science Education, Behavioral and Brain Sciences, Lecture notes in computer science and Creativity Research Journal.

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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