William Yeoh

1.8k citations
123 papers · 1.3k · h-index 18

Impact in

Papers in

William Yeoh

116 papers receiving 1.2k citations

Peers

William Yeoh
Comparison fields: 5 of 74
  • Signal Processing 365
  • Computer Networks and Communications 735
  • Management Science and Operations Research 299
  • Industrial and Manufacturing Engineering 194
  • Artificial Intelligence 473
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Citations per field
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Citations per year

Countries citing papers authored by William Yeoh

Since Specialization
Citations

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

Fields of papers citing papers by William Yeoh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 123 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018129
2 201267
3 200859
4 201740
5 201335
6 201033
7
Efficient incremental search for moving target search
200926
8
Goal recognition design with stochastic agent action outcomes
201625
9 201423
10 201423
11 201922
12 201821
13 201420
14 202219
15 201218
16 202018
17 201617
18 201017
19 201217
20 201116

About William Yeoh

William Yeoh is a scholar working on Computer Networks and Communications, Artificial Intelligence, Signal Processing, Management Science and Operations Research and Industrial and Manufacturing Engineering, having authored 123 papers that have together received 1.3k indexed citations. Recurring topics across this work include Constraint Satisfaction and Optimization (60 papers), Data Management and Algorithms (36 papers), AI-based Problem Solving and Planning (27 papers), Auction Theory and Applications (22 papers), Logic, Reasoning, and Knowledge (21 papers), Scheduling and Timetabling Solutions (14 papers), Multi-Agent Systems and Negotiation (12 papers) and Bayesian Modeling and Causal Inference (12 papers). The work is most often cited by research in Signal Processing (365 citations), Computer Networks and Communications (735 citations), Management Science and Operations Research (299 citations), Industrial and Manufacturing Engineering (194 citations) and Artificial Intelligence (473 citations). William Yeoh has collaborated with scholars based in United States, Singapore and Israel. Frequent co-authors include Ferdinando Fioretto, Enrico Pontelli, Sven Koenig, Xiaoxun Sun, Makoto Yokoo, Hoong Chuin Lau, Tran Cao Son, Pradeep Varakantham, Duc Thien Nguyen and Ariel Felner. Their work appears in journals such as Journal of Artificial Intelligence Research, Autonomous Agents and Multi-Agent Systems, Lecture notes in computer science, Theory and Practice of Logic Programming and Journal of Loss Prevention in the Process Industries.

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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