Jia-Yeong Tsay
- Mechanics of Materials top 10%
- Civil and Structural Engineering top 10%
- Statistics, Probability and Uncertainty top 2%
- Computational Theory and Mathematics top 10%
- Mechanical Engineering
- Co-authors
- Jasbir S. AroraJ.B. CardosoW. J. StuddenRalph BuncherEdward A. EmmettLoren A. AndersonArch CarsonVictor J. Elia
- Topics
- Manufacturing Process and Optimization (4 papers)Advanced Multi-Objective Optimization Algorithms (4 papers)Composite Structure Analysis and Optimization (4 papers)
- Cited by
- Statistics, Probability and UncertaintyChemical Health and SafetyCivil and Structural Engineering
- Journals
- Journal of the American Statistical AssociationComputer Methods in Applied Mechanics and EngineeringThe Annals of Statistics
- Partner nations
- United StatesCanada
In The Last Decade
Jia-Yeong Tsay
12 papers receiving 289 citations
Peers
Comparison fields: 5 of 61
- Mechanics of Materials 147
- Civil and Structural Engineering 142
- Statistics, Probability and Uncertainty 116
- Computational Theory and Mathematics 56
- Mechanical Engineering 50
Countries citing papers authored by Jia-Yeong Tsay
This map shows the geographic impact of Jia-Yeong Tsay'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 Jia-Yeong Tsay with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jia-Yeong Tsay more than expected).
Fields of papers citing papers by Jia-Yeong Tsay
This network shows the impact of papers produced by Jia-Yeong Tsay. 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 Jia-Yeong Tsay. The network helps show where Jia-Yeong Tsay may publish in the future.
Co-authorship network of co-authors of Jia-Yeong Tsay
This figure shows the co-authorship network connecting the top 25 collaborators of Jia-Yeong Tsay. A scholar is included among the top collaborators of Jia-Yeong Tsay 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 Jia-Yeong Tsay. Jia-Yeong Tsay is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 67 | |
| 3 | 147 | |
| 4 | 24 | |
| 5 | 2 | |
| 6 | 31 | |
| 7 | 1 | |
| 8 | 2 | |
| 9 | 5 | |
| 10 | 14 | |
| 11 | 22 | |
| 12 | THE ITERATIVE METHODS FOR CALCULATING OPTIMAL EXPERIMENTAL DESIGNS. | 3 |
About Jia-Yeong Tsay
Jia-Yeong Tsay is a scholar working on Chemical Health and Safety, Statistics, Probability and Uncertainty and Industrial and Manufacturing Engineering, having authored 12 papers that have together received 324 indexed citations. Recurring topics across this work include Manufacturing Process and Optimization (4 papers), Advanced Multi-Objective Optimization Algorithms (4 papers) and Composite Structure Analysis and Optimization (4 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (116 citations), Chemical Health and Safety (5 citations) and Civil and Structural Engineering (142 citations). Jia-Yeong Tsay has collaborated with scholars based in United States and Canada. Frequent co-authors include Jasbir S. Arora, J.B. Cardoso, W. J. Studden, Ralph Buncher, Edward A. Emmett, Loren A. Anderson, Arch Carson, Victor J. Elia, Stuart M. Brooks and Andrew Rau‐Chaplin. Their work appears in journals such as Journal of the American Statistical Association, Computer Methods in Applied Mechanics and Engineering and The Annals of Statistics.
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.