Rui Tuo

32 papers receiving 503 citations

Peers

Rui Tuo
Comparison fields: 5 of 86
  • Statistics, Probability and Uncertainty 215
  • Computational Theory and Mathematics 246
  • Management Science and Operations Research 122
  • Statistics and Probability 53
  • Artificial Intelligence 137
Replace Mickaël Binois with:
Mickaël Binois France
Domenico Spina Belgium
J.L. Maryak United States
Agnès Lagnoux France
Genetha A. Gray United States
Youssef Diouane France
Scott A. Starks United States
Leonid G. Khachiyan United States
Alex Gorodetsky United States
Rajan Srinivasan Netherlands
Rui Tuo relative to Mickaël Binois France Mickaël Binois's profile →
Citations per field
00.5×4.8×
Mickaël Binois · 1×
Citations per year

Countries citing papers authored by Rui Tuo

Since Specialization
Citations

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

Fields of papers citing papers by Rui Tuo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rui Tuo. 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 Rui Tuo. The network helps show where Rui Tuo may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201582
2 201476
3 201665
4 201335
5 201932
6 201330
7 201823
8 202018
9 201917
10 201616
11 202213
12 202413
13 202013
14 201611
15
Kriging Prediction with Isotropic Matern Correlations: Robustness and Experimental Designs
20209
16 20177
17 20216
18 20186
19 20226
20 20225

About Rui Tuo

Rui Tuo is a scholar working on Computational Theory and Mathematics, Statistics, Probability and Uncertainty, Artificial Intelligence, Management Science and Operations Research and Control and Systems Engineering, having authored 33 papers that have together received 519 indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (17 papers), Probabilistic and Robust Engineering Design (13 papers), Gaussian Processes and Bayesian Inference (9 papers), Control Systems and Identification (5 papers), Optimal Experimental Design Methods (5 papers), Simulation Techniques and Applications (4 papers), Numerical methods in inverse problems (2 papers) and Advanced Numerical Methods in Computational Mathematics (2 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (215 citations), Computational Theory and Mathematics (246 citations), Management Science and Operations Research (122 citations), Statistics and Probability (53 citations) and Artificial Intelligence (137 citations). Rui Tuo has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Changbao Wu, V. Roshan Joseph, C. F. Jeff Wu, Tirthankar Dasgupta, Cheng Wu, Matthew Plumlee, Wenjia Wang, Dan Yu, Yu Ding and Xu He. Their work appears in journals such as Technometrics, SIAM/ASA Journal on Uncertainty Quantification, IISE Transactions, Journal of the American Statistical Association and Statistica Sinica.

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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