Shan Ba

17 papers receiving 548 citations

Peers

Shan Ba
Comparison fields: 5 of 81
  • Statistics, Probability and Uncertainty 182
  • Management Science and Operations Research 213
  • Computational Theory and Mathematics 277
  • Industrial and Manufacturing Engineering 91
  • Statistics and Probability 31
Replace Ying Hung with:
Ying Hung United States
Mathieu Balesdent France
Mickaël Binois France
Julien Bect France
Yongdao Zhou China
Emmanuel Vázquez France
Quan Long China
Simon Mak United States
Andrey Pepelyshev United Kingdom
Loïc Brevault France
Shan Ba relative to Ying Hung United States Ying Hung's profile →
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Citations per year

Countries citing papers authored by Shan Ba

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 25 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.

Border = papers with Shan Ba Line = papers co-authored together Shan Ba links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 2015213
2 2014114
3 201287
4 201938
5 202132
6 201112
7 202112
8 202111
9 201810
10 20177
11 20177
12 20067
13 20136
14 20155
15 20223
16 20173
17 20061

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 17 papers that have together received 568 indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (9 papers), Optimal Experimental Design Methods (8 papers), Manufacturing Process and Optimization (3 papers), Probabilistic and Robust Engineering Design (3 papers), VLSI and FPGA Design Techniques (2 papers), Video Analysis and Summarization (2 papers), Gaussian Processes and Bayesian Inference (2 papers) and Advanced Clustering Algorithms Research (1 paper). The work is most often cited by research in Statistics, Probability and Uncertainty (182 citations), Management Science and Operations Research (213 citations), Computational Theory and Mathematics (277 citations), Industrial and Manufacturing Engineering (91 citations) and Statistics and Probability (31 citations). Shan Ba has collaborated with scholars based in United States, China and Netherlands. Frequent co-authors include V. Roshan Joseph, Evren Gul, William A. Brenneman, William R. Myers, Hao Yan, Li Gu, William Myers, Yongdong Zhang, Ying Jin and A. Krishna. Their work appears in journals such as Journal of Quality Technology, Technometrics, Biometrika, Journal of Biomechanical Engineering 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.

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