Shan Ba
Impact in
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- Probabilistic and Robust Engineering Design
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- Advanced Multi-Objective Optimization Algorithms
Papers in
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- Optimal Experimental Design Methods 8
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- Advanced Multi-Objective Optimization Algorithms 9
- Co-authors
- V. Roshan Joseph (8 shared papers)Evren Gul (2 shared papers)William A. Brenneman (5 shared papers)William R. Myers (4 shared papers)Hao Yan (1 shared paper)Li Gu (1 shared paper)A. Krishna (1 shared paper)Ramesh Singh (1 shared paper)
- Journals
- Journal of Quality Technology (5 papers)Technometrics (4 papers)Journal of Biomechanical Engineering (1 paper)The Annals of Applied Statistics (1 paper)Journal of the American Statistical Association (1 paper)
- Partner nations
- United StatesNetherlandsIndia
In The Last Decade
Shan Ba
15 papers receiving 503 citations
Peers
Comparison fields: 5 of 82
- Statistics, Probability and Uncertainty 168
- Computational Theory and Mathematics 261
- Management Science and Operations Research 200
- Industrial and Manufacturing Engineering 84
- Statistics and Probability 31
Countries citing papers authored by Shan Ba
This map shows the geographic impact of Shan Ba'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 Shan Ba with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shan Ba more than expected).
Fields of papers citing papers by Shan Ba
This network shows the impact of papers produced by Shan Ba. 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 Shan Ba. The network helps show where Shan Ba may publish in the future.
Co-authors
The 18 scholars most cited alongside Shan Ba, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 207 | |
| 2 | 2014 | 105 | |
| 3 | 2012 | 79 | |
| 4 | 2019 | 37 | |
| 5 | 2021 | 23 | |
| 6 | 2021 | 12 | |
| 7 | 2021 | 11 | |
| 8 | 2011 | 10 | |
| 9 | 2018 | 10 | |
| 10 | 2017 | 7 | |
| 11 | 2017 | 7 | |
| 12 | 2013 | 6 | |
| 13 | 2015 | 4 | |
| 14 | 2022 | 3 | |
| 15 | 2017 | 3 |
About Shan Ba
Shan Ba is a scholar working on Management Science and Operations Research, Computational Theory and Mathematics, Artificial Intelligence, Statistics, Probability and Uncertainty and Industrial and Manufacturing Engineering, having authored 15 papers that have together received 524 indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (9 papers), Optimal Experimental Design Methods (8 papers), Probabilistic and Robust Engineering Design (3 papers), Manufacturing Process and Optimization (3 papers), VLSI and FPGA Design Techniques (2 papers), Gaussian Processes and Bayesian Inference (2 papers), Face and Expression Recognition (1 paper) and Advanced machining processes and optimization (1 paper). The work is most often cited by research in Statistics, Probability and Uncertainty (168 citations), Computational Theory and Mathematics (261 citations), Management Science and Operations Research (200 citations), Industrial and Manufacturing Engineering (84 citations) and Statistics and Probability (31 citations). Shan Ba has collaborated with scholars based in United States, Netherlands and India. Frequent co-authors include V. Roshan Joseph, Evren Gul, William A. Brenneman, William R. Myers, Hao Yan, Li Gu, A. Krishna, Ramesh Singh, William Myers and Ran Jin. Their work appears in journals such as Journal of Quality Technology, Technometrics, Journal of Biomechanical Engineering, The Annals of Applied Statistics and Journal of the American Statistical Association.
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.