Ling-Yau Chan
- Statistics, Probability and Uncertainty top 2%
- Management Science and Operations Research top 5%
- Safety, Risk, Reliability and Quality top 5%
- Computational Theory and Mathematics top 10%
- Statistics and Probability top 5%
- Co-authors
- Shaomin WuTom RyanConnie W. C. HuiTony K.H. ChungJoseph KwongJacqueline Ho Sze LeeTat‐San LauChi Hang Wong
- Topics
- Optimal Experimental Design Methods (12 papers)Manufacturing Process and Optimization (8 papers)Advanced Multi-Objective Optimization Algorithms (6 papers)
- Cited by
- Statistics, Probability and UncertaintyManagement Science and Operations ResearchSafety, Risk, Reliability and Quality
- Partner nations
- Hong KongIndiaUnited Kingdom
In The Last Decade
Ling-Yau Chan
24 papers receiving 305 citations
Peers
Comparison fields: 5 of 75
- Statistics, Probability and Uncertainty 116
- Management Science and Operations Research 107
- Safety, Risk, Reliability and Quality 72
- Computational Theory and Mathematics 67
- Statistics and Probability 62
Countries citing papers authored by Ling-Yau Chan
This map shows the geographic impact of Ling-Yau Chan'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 Ling-Yau Chan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ling-Yau Chan more than expected).
Fields of papers citing papers by Ling-Yau Chan
This network shows the impact of papers produced by Ling-Yau Chan. 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 Ling-Yau Chan. The network helps show where Ling-Yau Chan may publish in the future.
Co-authorship network of co-authors of Ling-Yau Chan
This figure shows the co-authorship network connecting the top 25 collaborators of Ling-Yau Chan. A scholar is included among the top collaborators of Ling-Yau Chan 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 Ling-Yau Chan. Ling-Yau Chan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 71 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 17 | |
| 5 | 7 | |
| 6 | 16 | |
| 7 | 5 | |
| 8 | 9 | |
| 9 | 3 | |
| 10 | 69 | |
| 11 | 9 | |
| 12 | 3 | |
| 13 | 36 | |
| 14 | A-OPTIMAL DESIGNS FOR AN ADDITIVE QUADRATIC MIXTURE MODEL | 5 |
| 15 | 3 | |
| 16 | 8 | |
| 17 | 6 | |
| 18 | 1 | |
| 19 | 12 | |
| 20 | 4 |
About Ling-Yau Chan
Ling-Yau Chan is a scholar working on Statistics, Probability and Uncertainty, Management Science and Operations Research and Statistics and Probability, having authored 24 papers that have together received 320 indexed citations. Recurring topics across this work include Optimal Experimental Design Methods (12 papers), Manufacturing Process and Optimization (8 papers) and Advanced Multi-Objective Optimization Algorithms (6 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (116 citations), Management Science and Operations Research (107 citations) and Safety, Risk, Reliability and Quality (72 citations). Ling-Yau Chan has collaborated with scholars based in Hong Kong, India and United Kingdom. Frequent co-authors include Shaomin Wu, Tom Ryan, Connie W. C. Hui, Tony K.H. Chung, Joseph Kwong, Jacqueline Ho Sze Lee, Tat‐San Lau, Chi Hang Wong, Gennian Ge and Mingyao Ai. Their work appears in journals such as Oncogene, Biometrika and Journal of Mathematical Analysis and Applications.
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.