William Yeoh

1.7k total citations
97 papers, 921 citations indexed

About

William Yeoh is a scholar working on Computer Networks and Communications, Artificial Intelligence and Signal Processing. According to data from OpenAlex, William Yeoh has authored 97 papers receiving a total of 921 indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Computer Networks and Communications, 52 papers in Artificial Intelligence and 29 papers in Signal Processing. Recurrent topics in William Yeoh's work include Constraint Satisfaction and Optimization (48 papers), Data Management and Algorithms (28 papers) and AI-based Problem Solving and Planning (19 papers). William Yeoh is often cited by papers focused on Constraint Satisfaction and Optimization (48 papers), Data Management and Algorithms (28 papers) and AI-based Problem Solving and Planning (19 papers). William Yeoh collaborates with scholars based in United States, Singapore and Israel. William Yeoh's co-authors include Sven Koenig, Enrico Pontelli, Ferdinando Fioretto, Xiaoxun Sun, Hoong Chuin Lau, Makoto Yokoo, Pradeep Varakantham, Duc Thien Nguyen, Tran Cao Son and Ping Hou and has published in prestigious journals such as Environmental Science & Technology, Artificial Intelligence and Engineering Applications of Artificial Intelligence.

In The Last Decade

William Yeoh

90 papers receiving 894 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
William Yeoh United States 16 531 347 269 208 165 97 921
Roman Barták Czechia 16 384 0.7× 396 1.1× 79 0.3× 119 0.6× 231 1.4× 143 899
Pragnesh Jay Modi United States 14 757 1.4× 453 1.3× 338 1.3× 278 1.3× 54 0.3× 30 1.0k
Jonathan P. Pearce United States 14 598 1.1× 283 0.8× 291 1.1× 243 1.2× 27 0.2× 24 955
Sven Hartmann Germany 18 516 1.0× 496 1.4× 305 1.1× 169 0.8× 27 0.2× 119 955
Habiba Drias Algeria 17 209 0.4× 434 1.3× 116 0.4× 85 0.4× 115 0.7× 120 880
Danny Raz Israel 23 1.9k 3.5× 196 0.6× 59 0.2× 79 0.4× 71 0.4× 81 2.1k
Yanbin Sun China 16 557 1.0× 461 1.3× 211 0.8× 24 0.1× 146 0.9× 65 1.2k
Christos Zaroliagis Greece 15 324 0.6× 134 0.4× 328 1.2× 31 0.1× 168 1.0× 84 958
Zuohua Ding China 16 267 0.5× 320 0.9× 43 0.2× 37 0.2× 171 1.0× 129 1.0k
Hui Ma New Zealand 17 578 1.1× 300 0.9× 138 0.5× 35 0.2× 51 0.3× 109 942

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-authorship network of co-authors of William Yeoh

This figure shows the co-authorship network connecting the top 25 collaborators of William Yeoh. A scholar is included among the top collaborators of William Yeoh 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 William Yeoh. William Yeoh 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.
Yeoh, William, et al.. (2024). Dialectical Reconciliation via Structured Argumentative Dialogues. 777–787. 1 indexed citations
2.
Yeoh, William, et al.. (2023). A particle swarm inspired approach for continuous distributed constraint optimization problems. Engineering Applications of Artificial Intelligence. 123. 106280–106280. 1 indexed citations
3.
Son, Tran Cao, William Yeoh, Roni Stern, & Meir Kalech. (2023). Multi-Agent Planning and Diagnosis with Commonsense Reasoning. 1–9.
4.
Hernández, Carlos, et al.. (2022). Simple and efficient bi-objective search algorithms via fast dominance checks. Artificial Intelligence. 314. 103807–103807. 16 indexed citations
5.
Zivan, Roie, et al.. (2021). Latency-Aware Local Search for Distributed Constraint Optimization. Autonomous Agents and Multi-Agent Systems. 1019–1027. 3 indexed citations
6.
Zivan, Roie, et al.. (2021). The Effect of Asynchronous Execution and Message Latency on Max-Sum. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 2 indexed citations
7.
Yeoh, William, et al.. (2020). New Algorithms for Continuous Distributed Constraint Optimization Problems. 502–510. 8 indexed citations
8.
Han, The Anh, et al.. (2018). Preference Elicitation with Interdependency and User Bother Cost. ePrints Soton (University of Southampton). 1459–1467. 8 indexed citations
9.
Zha, Yabing, et al.. (2018). Inverse Reinforcement Learning Based Human Behavior Modeling for Goal Recognition in Dynamic Local Network Interdiction.. National Conference on Artificial Intelligence. 646–653. 8 indexed citations
10.
Fioretto, Ferdinando, William Yeoh, & Enrico Pontelli. (2017). A Multiagent System Approach to Scheduling Devices in Smart Homes. National Conference on Artificial Intelligence. 981–989. 12 indexed citations
11.
Hou, Ping, et al.. (2017). Infinite-Horizon Proactive Dynamic DCOPs. Adaptive Agents and Multi-Agents Systems. 212–220. 7 indexed citations
12.
Hou, Ping, et al.. (2016). Goal recognition design with stochastic agent action outcomes. International Joint Conference on Artificial Intelligence. 3279–3285. 23 indexed citations
13.
Fioretto, Ferdinando, et al.. (2014). GD-GIBBS: a GPU-based sampling algorithm for solving distributed constraint optimization problems. Adaptive Agents and Multi-Agents Systems. 1339–1340. 5 indexed citations
14.
Varakantham, Pradeep, William Yeoh, Prasanna Velagapudi, Katia Sycara, & Paul Scerri. (2012). Prioritized shaping of models for solving DEC-POMDPs. Adaptive Agents and Multi-Agents Systems. 3. 1269–1270. 1 indexed citations
15.
Yeoh, William, Pradeep Varakantham, Xiaoxun Sun, & Sven Koenig. (2011). Incremental DCOP search algorithms for solving dynamic DCOPs. Adaptive Agents and Multi-Agents Systems. 1069–1070. 14 indexed citations
16.
Sun, Xiaoxun, William Yeoh, & Sven Koenig. (2010). Generalized Fringe-Retrieving A*: faster moving target search on state lattices. Adaptive Agents and Multi-Agents Systems. 1081–1088. 15 indexed citations
17.
Sun, Xiaoxun, William Yeoh, & Sven Koenig. (2010). Moving target D* Lite. Adaptive Agents and Multi-Agents Systems. 67–74. 28 indexed citations
18.
Yeoh, William, Xiaoxun Sun, & Sven Koenig. (2009). Trading off solution quality for faster computation in DCOP search algorithms. International Joint Conference on Artificial Intelligence. 354–360. 12 indexed citations
19.
Sun, Xiaoxun, William Yeoh, & Sven Koenig. (2009). Efficient incremental search for moving target search. International Joint Conference on Artificial Intelligence. 615–620. 24 indexed citations
20.
Yeoh, William, Sven Koenig, & Xiaoxun Sun. (2008). Trading off solution cost for smaller runtime in DCOP search algorithms. Adaptive Agents and Multi-Agents Systems. 1445–1448.

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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