Jin Xiao

2.9k total citations
83 papers, 2.0k citations indexed

About

Jin Xiao is a scholar working on Artificial Intelligence, Marketing and Management Science and Operations Research. According to data from OpenAlex, Jin Xiao has authored 83 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Artificial Intelligence, 15 papers in Marketing and 14 papers in Management Science and Operations Research. Recurrent topics in Jin Xiao's work include Imbalanced Data Classification Techniques (24 papers), Statistical and Computational Modeling (17 papers) and Financial Distress and Bankruptcy Prediction (13 papers). Jin Xiao is often cited by papers focused on Imbalanced Data Classification Techniques (24 papers), Statistical and Computational Modeling (17 papers) and Financial Distress and Bankruptcy Prediction (13 papers). Jin Xiao collaborates with scholars based in China, Germany and Hong Kong. Jin Xiao's co-authors include Ling Xie, Xiaoyi Jiang, Shouyang Wang, Changzheng He, Yi Xiao, Yi Hu, Geer Teng, Bing Zhu, Guohao Li and Jing Huang and has published in prestigious journals such as Journal of Cleaner Production, Scientific Reports and Journal of Business Research.

In The Last Decade

Jin Xiao

80 papers receiving 1.9k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Jin Xiao	646	358	278	272	225	83	2.0k
William Remus	467 0.7×	277 0.8×	267 1.0×	922 3.4×	93 0.4×	65	2.2k
Shuai Zhang	749 1.2×	178 0.5×	812 2.9×	485 1.8×	314 1.4×	172	3.7k
Fred Collopy	295 0.5×	246 0.7×	208 0.7×	732 2.7×	72 0.3×	46	1.9k
Marcus O’Connor	440 0.7×	482 1.3×	317 1.1×	1.8k 6.5×	100 0.4×	56	2.8k
Chih‐Hung Wu	566 0.9×	165 0.5×	242 0.9×	614 2.3×	163 0.7×	97	2.6k
Changyong Liang	744 1.2×	102 0.3×	103 0.4×	900 3.3×	44 0.2×	144	3.0k
Ching‐Ter Chang	427 0.7×	456 1.3×	396 1.4×	1.2k 4.5×	41 0.2×	127	4.4k
Emmanuel Sirimal Silva	434 0.7×	333 0.9×	142 0.5×	498 1.8×	44 0.2×	67	2.4k
Malcolm J. Beynon	512 0.8×	399 1.1×	44 0.2×	789 2.9×	240 1.1×	100	3.2k
Murtaza Haider	431 0.7×	281 0.8×	69 0.2×	541 2.0×	47 0.2×	36	3.0k

Countries citing papers authored by Jin Xiao

Since Specialization

Citations

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

Fields of papers citing papers by Jin Xiao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jin Xiao

This figure shows the co-authorship network connecting the top 25 collaborators of Jin Xiao. A scholar is included among the top collaborators of Jin Xiao 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 Jin Xiao. Jin Xiao 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

Xiao, Jin, Sihan Li, Yuhang Tian, et al.. (2025). Example dependent cost sensitive learning based selective deep ensemble model for customer credit scoring. Scientific Reports. 15(1). 6000–6000. 2 indexed citations

Xiao, Jin, et al.. (2024). Optimising allocation of marketing resources among offline channel retailers: A bi-clustering-based model. Journal of Business Research. 186. 114914–114914. 1 indexed citations

Wang, Yadong, et al.. (2024). Deep reinforcement learning based on balanced stratified prioritized experience replay for customer credit scoring in peer-to-peer lending. Artificial Intelligence Review. 57(4). 8 indexed citations

Xiao, Jin, et al.. (2024). ProNet DB: a proteome-wise database for protein surface property representations and RNA-binding profiles. Database. 2024.

Zhu, Bing, Qian Cheng, Seppe vanden Broucke, Jin Xiao, & Yuanyuan Li. (2023). A bagging-based selective ensemble model for churn prediction on imbalanced data. Expert Systems with Applications. 227. 120223–120223. 11 indexed citations

Li, Guohao, Miaomiao Niu, Jin Xiao, Jiaqian Wu, & Jinkai Li. (2023). The rebound effect of decarbonization in China’s power sector under the carbon trading scheme. Energy Policy. 177. 113543–113543. 13 indexed citations

Xiao, Jin, et al.. (2023). A novel federated learning approach with knowledge transfer for credit scoring. Decision Support Systems. 177. 114084–114084. 24 indexed citations

Wang, Yadong, et al.. (2023). Balanced incremental deep reinforcement learning based on variational autoencoder data augmentation for customer credit scoring. Engineering Applications of Artificial Intelligence. 122. 106056–106056. 8 indexed citations

Xiao, Jin, et al.. (2023). Black-Box Attack-Based Security Evaluation Framework for Credit Card Fraud Detection Models. INFORMS journal on computing. 35(5). 986–1001. 7 indexed citations

10.

Xiao, Jin, et al.. (2023). A novel deep ensemble model for imbalanced credit scoring in internet finance. International Journal of Forecasting. 40(1). 348–372. 16 indexed citations

11.

Yan, Yang, et al.. (2023). Complex-Valued GMDH-Based Data Characteristic-Driven Adaptive Decision Support System for Customer Classification. IEEE Transactions on Systems Man and Cybernetics Systems. 54(1). 403–415. 4 indexed citations

12.

Wang, Yadong, et al.. (2022). Deep reinforcement learning with the confusion-matrix-based dynamic reward function for customer credit scoring. Expert Systems with Applications. 200. 117013–117013. 47 indexed citations

13.

Xu, Lixiang, Xiaofeng Wang, Lu Bai, et al.. (2020). Probabilistic SVM classifier ensemble selection based on GMDH-type neural network. Pattern Recognition. 106. 107373–107373. 24 indexed citations

14.

Xiao, Jin, et al.. (2019). A Hybrid Classification Framework Based on Clustering. IEEE Transactions on Industrial Informatics. 16(4). 2177–2188. 23 indexed citations

15.

Teng, Geer, et al.. (2019). DESIGN AND DEVELOPMENT OF HUMAN COMPUTER INTERFACE USING ELECTROOCULOGRAM WITH DEEP LEARNING. Artificial Intelligence in Medicine. 102. 101765–101765. 22 indexed citations

16.

Teng, Geer, Jin Xiao, Yue He, Tingting Zheng, & Changzheng He. (2017). Use of group method of data handling for transport energy demand modeling. Energy Science & Engineering. 5(5). 302–317. 33 indexed citations

17.

Xie, Ling, Jin Xiao, Yi Hu, Hengjun Zhao, & Yi Xiao. (2017). China’s energy consumption forecasting by GMDH based auto-regressive model. Journal of Systems Science and Complexity. 30(6). 1332–1349. 7 indexed citations

18.

Xiao, Jin, Yi Hu, Yi Xiao, Lixiang Xu, & Shouyang Wang. (2016). A hybrid transfer learning model for crude oil price forecasting. Statistics and Its Interface. 10(1). 119–130. 5 indexed citations

19.

Xiao, Jin, et al.. (2014). One‐Step Dynamic Classifier Ensemble Model for Customer Value Segmentation with Missing Values. Mathematical Problems in Engineering. 2014(1). 4 indexed citations

20.

Xiao, Jin, Changzheng He, & Xiaoyi Jiang. (2009). Structure identification of Bayesian classifiers based on GMDH. Knowledge-Based Systems. 22(6). 461–470. 33 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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