C. Devon Lin

21 papers receiving 230 citations

Peers

C. Devon Lin
Comparison fields: 5 of 58
  • Management Science and Operations Research 156
  • Computational Theory and Mathematics 163
  • Statistics, Probability and Uncertainty 56
  • Industrial and Manufacturing Engineering 34
  • Statistics and Probability 22
Replace K. H. V. Booth with:
K. H. V. Booth United Kingdom
Arjen P.A. Vestjens Netherlands
Kyoichi Nakashima Japan
Mardé Helbig South Africa
Evsey Morozov Russia
Xingxing He China
Jia-Jie Zhu China
Robert Valette France
Christian W. G. Lasarczyk Germany
Ivo Nowak Germany
C. Devon Lin relative to K. H. V. Booth United Kingdom K. H. V. Booth's profile →
Citations per field
00.5×10×12.7×
K. H. V. Booth · 1×
Citations per year

Countries citing papers authored by C. Devon Lin

Since Specialization
Citations

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

Fields of papers citing papers by C. Devon Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by C. Devon Lin. 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 C. Devon Lin. The network helps show where C. Devon Lin may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201651
2 201447
3
A NEW AND FLEXIBLE METHOD FOR CONSTRUCTING DESIGNS FOR COMPUTER EXPERIMENTS
201640
4 201426
5 201220
6 20158
7 20178
8 20216
9 20176
10 20196
11 20125
12 20194
13 20172
14 20132
15 20192
16 20112
17 20062
18 20192
19 20231
20 20221

About C. Devon Lin

C. Devon Lin is a scholar working on Computational Theory and Mathematics, Management Science and Operations Research, Artificial Intelligence, Statistics, Probability and Uncertainty and Statistics and Probability, having authored 22 papers that have together received 242 indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (16 papers), Optimal Experimental Design Methods (14 papers), Probabilistic and Robust Engineering Design (5 papers), Manufacturing Process and Optimization (3 papers), Gaussian Processes and Bayesian Inference (3 papers), VLSI and FPGA Design Techniques (2 papers), Evolutionary Algorithms and Applications (2 papers) and Statistical Methods and Bayesian Inference (2 papers). The work is most often cited by research in Management Science and Operations Research (156 citations), Computational Theory and Mathematics (163 citations), Statistics, Probability and Uncertainty (56 citations), Industrial and Manufacturing Engineering (34 citations) and Statistics and Probability (22 citations). C. Devon Lin has collaborated with scholars based in Canada, United States and China. Frequent co-authors include Xinwei Deng, Derek Bingham, R. Kerry Rowe, R. R. Sitter, Ying Hung, Michael S. Hamada, Leslie M. Moore, Christine M. Anderson‐Cook, Fasheng Sun and Yuanzhen He. Their work appears in journals such as Statistica Sinica, Journal of Statistical Planning and Inference, Technometrics, Canadian Journal of Statistics and Bernoulli.

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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