Bing‐Chang Wang

1.2k total citations
73 papers, 825 citations indexed

About

Bing‐Chang Wang is a scholar working on Finance, Economics and Econometrics and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Bing‐Chang Wang has authored 73 papers receiving a total of 825 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Finance, 19 papers in Economics and Econometrics and 17 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Bing‐Chang Wang's work include Stochastic processes and financial applications (30 papers), Mathematical and Theoretical Epidemiology and Ecology Models (17 papers) and Distributed Control Multi-Agent Systems (15 papers). Bing‐Chang Wang is often cited by papers focused on Stochastic processes and financial applications (30 papers), Mathematical and Theoretical Epidemiology and Ecology Models (17 papers) and Distributed Control Multi-Agent Systems (15 papers). Bing‐Chang Wang collaborates with scholars based in China, Australia and Canada. Bing‐Chang Wang's co-authors include Ji‐Feng Zhang, Huanshui Zhang, Minyi Huang, Jianhui Huang, Minyue Fu, Tongwen Chen, Xiangyu Meng, Seeram Ramakrishna, Yibing Sun and Yining Ding and has published in prestigious journals such as IEEE Transactions on Automatic Control, Automatica and Journal of Colloid and Interface Science.

In The Last Decade

Bing‐Chang Wang

58 papers receiving 799 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Bing‐Chang Wang China 16 313 212 201 190 103 73 825
Xiushan Jiang China 10 88 0.3× 63 0.3× 35 0.2× 188 1.0× 32 0.3× 33 361
Francesca Parise United States 14 29 0.1× 195 0.9× 115 0.6× 108 0.6× 103 1.0× 43 690
Claude Lefèvre Belgium 19 215 0.7× 16 0.1× 213 1.1× 68 0.4× 30 0.3× 82 1.1k
Sérgio Adriani David Brazil 16 72 0.2× 32 0.2× 234 1.2× 69 0.4× 103 1.0× 45 603
Xiaofei Li China 12 52 0.2× 45 0.2× 30 0.1× 14 0.1× 50 0.5× 61 510
Daniel Andersson Sweden 7 183 0.6× 5 0.0× 69 0.3× 47 0.2× 20 0.2× 27 330
Hailiang Yang China 17 232 0.7× 95 0.4× 287 1.4× 78 0.4× 6 0.1× 63 1.0k
Gonçalo dos Reis United Kingdom 16 301 1.0× 15 0.1× 82 0.4× 158 0.8× 37 0.4× 43 1.3k
Nicolas Langrené Australia 12 148 0.5× 12 0.1× 54 0.3× 33 0.2× 32 0.3× 29 462

Countries citing papers authored by Bing‐Chang Wang

Since Specialization
Citations

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

Fields of papers citing papers by Bing‐Chang Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bing‐Chang Wang. 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 Bing‐Chang Wang. The network helps show where Bing‐Chang Wang may publish in the future.

Co-authorship network of co-authors of Bing‐Chang Wang

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

All Works

20 of 20 papers shown
1.
Wang, Bing‐Chang, et al.. (2025). Data-Driven Mean-Field Equilibrium Computation in Large-Population LQG Games. IEEE Transactions on Control of Network Systems. 12(4). 2713–2725.
2.
Wang, Bing‐Chang. (2025). Mean field hierarchical control for production output adjustment with noisy sticky prices. Automatica. 176. 112260–112260. 1 indexed citations
3.
Wang, Bing‐Chang, et al.. (2024). Discrete-time indefinite linear-quadratic mean field games and control: The finite-population case. Automatica. 162. 111518–111518. 3 indexed citations
4.
Wang, Bing‐Chang, et al.. (2024). Asymptotically Optimal Distributed Control for Linear–Quadratic Mean Field Social Systems With Heterogeneous Agents. IEEE Transactions on Automatic Control. 70(5). 3197–3212.
5.
Wang, Bing‐Chang, et al.. (2024). Mean field LQG social optimization: A reinforcement learning approach. Automatica. 172. 111924–111924.
6.
Wang, Bing‐Chang & Minyi Huang. (2023). Mean Field Social Control for Production Output Adjustment with Noisy Sticky Prices. Dynamic Games and Applications. 14(3). 716–732. 2 indexed citations
7.
Wang, Bing‐Chang, et al.. (2023). Open-Loop Saddle Points for Irregular Linear-Quadratic Two-Person Zero-Sum Games. 2. 7214–7219.
8.
Ding, Yining, Ziyi Zhou, Bing‐Chang Wang, et al.. (2022). Icy core–shell composite nanofibers with cooling, antibacterial and healing properties for outdoor burns. Journal of Colloid and Interface Science. 629(Pt B). 206–216. 11 indexed citations
9.
Wang, Bing‐Chang, et al.. (2022). Robust Mean Field Linear Quadratic Social Control: Open-Loop and Closed-Loop Strategies. SIAM Journal on Control and Optimization. 60(4). 2184–2213. 4 indexed citations
10.
Wang, Bing‐Chang, et al.. (2021). Robust linear quadratic mean field social control: A direct approach. ESAIM Control Optimisation and Calculus of Variations. 27. 20–20. 5 indexed citations
11.
Huang, Jianhui, Bing‐Chang Wang, & Jiongmin Yong. (2021). Social Optima in Mean Field Linear-Quadratic-Gaussian Control with Volatility Uncertainty. SIAM Journal on Control and Optimization. 59(2). 825–856. 14 indexed citations
12.
Wang, Bing‐Chang, et al.. (2021). Finite and infinite clusters mean field control problems via graphon theory. 2021 China Automation Congress (CAC). 5986–5990.
13.
Huang, Jianhui, et al.. (2020). Social optima in leader-follower mean field linear quadratic control. ESAIM Control Optimisation and Calculus of Variations. 27. S12–S12. 9 indexed citations
14.
Wang, Bing‐Chang & Ji‐Feng Zhang. (2017). Social Optima in Mean Field Linear-Quadratic-Gaussian Models with Markov Jump Parameters. SIAM Journal on Control and Optimization. 55(1). 429–456. 60 indexed citations
15.
Wang, Bing‐Chang & Minyi Huang. (2015). Dynamic production output adjustment with sticky prices: A mean field game approach. 76. 4438–4443. 8 indexed citations
16.
Wang, Bing‐Chang, Xiangyu Meng, & Tongwen Chen. (2014). Event Based Pulse-Modulated Control of Linear Stochastic Systems. IEEE Transactions on Automatic Control. 59(8). 2144–2150. 40 indexed citations
17.
Wang, Bing‐Chang & Ji‐Feng Zhang. (2012). Stackelberg games of large population multi-agent systems: Centralized and distributed strategies. Chinese Control Conference. 6303–6308.
18.
Wang, Bing‐Chang & Ji‐Feng Zhang. (2010). Mean field games for large population stochastic multi-agent systems with Markov jumps. Chinese Control Conference. 4572–4577. 1 indexed citations
19.
Wang, Bing‐Chang & Ji‐Feng Zhang. (2009). Consensus Conditions of Multi-Agent Systems with Unbalanced Topology and Stochastic Disturbances. Xitong kexue yu shuxue. 29(10). 1353. 21 indexed citations
20.
Wang, Bing‐Chang. (2008). A Class of Markov-Modulated Continuous Infectious Disease Model. Journal of Biomathematics.

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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