Chao Bian

444 total citations
22 papers, 184 citations indexed

About

Chao Bian is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Management Science and Operations Research. According to data from OpenAlex, Chao Bian has authored 22 papers receiving a total of 184 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 16 papers in Computational Theory and Mathematics and 3 papers in Management Science and Operations Research. Recurrent topics in Chao Bian's work include Advanced Multi-Objective Optimization Algorithms (15 papers), Metaheuristic Optimization Algorithms Research (13 papers) and Evolutionary Algorithms and Applications (12 papers). Chao Bian is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (15 papers), Metaheuristic Optimization Algorithms Research (13 papers) and Evolutionary Algorithms and Applications (12 papers). Chao Bian collaborates with scholars based in China, United Kingdom and Australia. Chao Bian's co-authors include Chao Qian, Ke Tang, Yang Yu, Miqing Li, Chao Feng, Shuangzhi Wu, Weilong Dong, Deyi Xiong, Minghui Xu and Xin Yao and has published in prestigious journals such as Artificial Intelligence, IEEE Transactions on Evolutionary Computation and Applied Sciences.

In The Last Decade

Chao Bian

21 papers receiving 182 citations

Peers

Chao Bian

CTM

CNC

CVPR

CSE

Verena Heidrich-Meisner Germany

Ashutosh Trivedi United States

Alfons Geser Germany

Nicholas Holden United Kingdom

G. Sivakumar India

Ralf Wimmer Germany

Victor Vu United States

Tran Viet Xuan Phuong Australia

Deevashwer Rathee India

Ming Tan United States

Verena Heidrich-Meisner Germany

Chao Bian

125 ×0.9

43 ×0.4

CTM

13 ×1.1

CNC

7 ×0.6

CVPR

13 ×1.3

CSE

Citations per year, relative to Chao Bian Chao Bian (= 1×) peers Verena Heidrich-Meisner

Countries citing papers authored by Chao Bian

Since Specialization

Citations

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

Fields of papers citing papers by Chao Bian

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chao Bian

This figure shows the co-authorship network connecting the top 25 collaborators of Chao Bian. A scholar is included among the top collaborators of Chao Bian 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 Chao Bian. Chao Bian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Bian, Chao, et al.. (2025). Stochastic population update can provably be helpful in multi-objective evolutionary algorithms. Artificial Intelligence. 341. 104308–104308. 2 indexed citations

Bian, Chao, Shi‐Bin Ren, Miqing Li, & Chao Qian. (2025). An Archive Can Bring Provable Speed-ups in Multi-Objective Evolutionary Algorithms. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 13–14. 1 indexed citations

Bian, Chao, et al.. (2024). Towards Running Time Analysis of Interactive Multi-Objective Evolutionary Algorithms. Proceedings of the AAAI Conference on Artificial Intelligence. 38(18). 20777–20785. 2 indexed citations

Cai, Hui, Chao Bian, Biyun Sheng, et al.. (2024). QuoTa: An Online Quality-Aware Incentive Mechanism for Fast Federated Learning. Applied Sciences. 14(2). 833–833. 2 indexed citations

Bian, Chao, et al.. (2023). Submodular Maximization under the Intersection of Matroid and Knapsack Constraints. Proceedings of the AAAI Conference on Artificial Intelligence. 37(4). 3959–3967. 2 indexed citations

Bian, Chao, et al.. (2023). Stochastic Population Update Can Provably Be Helpful in Multi-Objective Evolutionary Algorithms. University of Birmingham Research Portal (University of Birmingham). 5513–5521. 22 indexed citations

Xu, Minghui, et al.. (2023). DEPN: Detecting and Editing Privacy Neurons in Pretrained Language Models. 2875–2886. 12 indexed citations

Wu, Shuangzhi, et al.. (2023). Enhancing Dialogue Summarization with Topic-Aware Global- and Local- Level Centrality. 27–38. 5 indexed citations

Bian, Chao, et al.. (2023). Subset Selection for Evolutionary Multiobjective Optimization. IEEE Transactions on Evolutionary Computation. 28(2). 403–417. 10 indexed citations

10.

Bian, Chao, et al.. (2022). Robust Subset Selection by Greedy and Evolutionary Pareto Optimization. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. 4726–4732. 2 indexed citations

11.

Bian, Chao, Chao Qian, Frank Neumann, & Yang Yu. (2021). Fast Pareto Optimization for Subset Selection with Dynamic Cost Constraints. 2191–2197. 3 indexed citations

12.

Bian, Chao, Chao Qian, Yang Yu, & Ke Tang. (2021). On the robustness of median sampling in noisy evolutionary optimization. Science China Information Sciences. 64(5). 11 indexed citations

13.

Bian, Chao, Chao Feng, Chao Qian, & Yang Yu. (2020). An Efficient Evolutionary Algorithm for Subset Selection with General Cost Constraints. Proceedings of the AAAI Conference on Artificial Intelligence. 34(4). 3267–3274. 22 indexed citations

14.

Qian, Chao, et al.. (2020). Subset Selection by Pareto Optimization with Recombination. Proceedings of the AAAI Conference on Artificial Intelligence. 34(3). 2408–2415. 17 indexed citations

15.

Qian, Chao, Chao Bian, Yang Yu, Ke Tang, & Xin Yao. (2020). Analysis of Noisy Evolutionary Optimization When Sampling Fails. Algorithmica. 83(4). 940–975. 7 indexed citations

16.

Qian, Chao, et al.. (2018). Running Time Analysis of the ( $$1+1$$ 1 + 1 )-EA for OneMax and LeadingOnes Under Bit-Wise Noise. Algorithmica. 81(2). 749–795. 17 indexed citations

17.

Bian, Chao, Chao Qian, & Ke Tang. (2018). A General Approach to Running Time Analysis of Multi-objective Evolutionary Algorithms. 1405–1411. 24 indexed citations

18.

Qian, Chao, et al.. (2017). Running time analysis of the (1+1)-EA for onemax and leadingones under bit-wise noise. Proceedings of the Genetic and Evolutionary Computation Conference. 1399–1406. 9 indexed citations

19.

Bian, Chao. (2008). Information Hiding Algorithm Based on N dimensions Arnold and DCT Transform. Communications technology.

20.

Liu, Zihong, et al.. (2005). Characterizing Transmission and Control of the SARS Epidemic: Novel Stochastic Spatio-Temporal Models. PubMed. 2005. 7463–7469. 3 indexed citations

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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