Xin Han

1.1k total citations · 2 hit papers
19 papers, 858 citations indexed

About

Xin Han is a scholar working on Artificial Intelligence, Sociology and Political Science and Computer Vision and Pattern Recognition. According to data from OpenAlex, Xin Han has authored 19 papers receiving a total of 858 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 4 papers in Sociology and Political Science and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Xin Han's work include Product Development and Customization (4 papers), Design Education and Practice (4 papers) and Sparse and Compressive Sensing Techniques (3 papers). Xin Han is often cited by papers focused on Product Development and Customization (4 papers), Design Education and Practice (4 papers) and Sparse and Compressive Sensing Techniques (3 papers). Xin Han collaborates with scholars based in China, Australia and United Kingdom. Xin Han's co-authors include Shengfeng Qin, Guofu Ding, Haizhu Zhang, Gang Li, Rob Law, Rong Li, Davis Ka Chio Fong, Jian Wang, Rong Li and Xing He and has published in prestigious journals such as Annals of Tourism Research, Pattern Recognition and IEEE Transactions on Neural Networks and Learning Systems.

In The Last Decade

Xin Han

18 papers receiving 835 citations

Hit Papers

Customization design method for complex product systems b... 2019 2026 2021 2023 2019 2019 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xin Han China 9 214 201 101 84 83 19 858
Graham Coates United Kingdom 17 115 0.5× 199 1.0× 22 0.2× 59 0.7× 189 2.3× 76 1.2k
Hong-Chul Lee South Korea 18 85 0.4× 136 0.7× 27 0.3× 143 1.7× 36 0.4× 84 959
Yingchao Zhang China 16 59 0.3× 88 0.4× 34 0.3× 124 1.5× 17 0.2× 72 825
Li Zhou China 18 40 0.2× 212 1.1× 211 2.1× 91 1.1× 31 0.4× 122 1.2k
Ėric Châtelet France 26 84 0.4× 295 1.5× 74 0.7× 58 0.7× 18 0.2× 92 2.2k
Qingfeng Meng China 19 40 0.2× 378 1.9× 70 0.7× 39 0.5× 16 0.2× 76 1.3k
Simona Dziţac Romania 15 72 0.3× 73 0.4× 42 0.4× 109 1.3× 14 0.2× 57 913
Chao Liang United States 18 308 1.4× 60 0.3× 26 0.3× 126 1.5× 20 0.2× 53 1.7k
Kuo-Hao Chang Taiwan 20 24 0.1× 141 0.7× 78 0.8× 113 1.3× 38 0.5× 83 1.5k

Countries citing papers authored by Xin Han

Since Specialization
Citations

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

Fields of papers citing papers by Xin Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xin Han

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

All Works

19 of 19 papers shown
1.
Han, Xin, et al.. (2023). A distributed neurodynamic algorithm for sparse signal reconstruction via 1-minimization. Neurocomputing. 550. 126480–126480. 5 indexed citations
2.
Han, Xin, Xing He, Mingliang Zhou, & Tingwen Huang. (2023). Inverse-free distributed neurodynamic optimization algorithms for sparse reconstruction. Signal Processing. 218. 109360–109360. 1 indexed citations
3.
Han, Xin, et al.. (2023). Distributed Neurodynamic Models for Solving a Class of System of Nonlinear Equations. IEEE Transactions on Neural Networks and Learning Systems. 36(1). 486–497. 2 indexed citations
4.
Han, Xin, Ye Zhu, Kai Ming Ting, & Gang Li. (2023). The impact of isolation kernel on agglomerative hierarchical clustering algorithms. Pattern Recognition. 139. 109517–109517. 12 indexed citations
5.
Han, Xin, Ye Zhu, Kai Ming Ting, De‐Chuan Zhan, & Gang Li. (2022). Streaming Hierarchical Clustering Based on Point-Set Kernel. Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 525–533. 5 indexed citations
6.
He, Xing, et al.. (2022). A Two-Layer Distributed Algorithm Using Neurodynamic System for Solving L 1-Minimization. IEEE Transactions on Circuits & Systems II Express Briefs. 69(8). 3490–3494. 7 indexed citations
7.
Wang, Jinlong, et al.. (2021). Systematic evaluation of abnormal detection methods on gas well sensor data. 1–6. 1 indexed citations
8.
Han, Xin, et al.. (2021). Research on the integration and optimization of MOOC teaching resources based on deep reinforcement learning. International Journal of Continuing Engineering Education and Life-Long Learning. 1(1). 1–1. 1 indexed citations
9.
Li, Chuandong, et al.. (2021). Neurodynamic Network for Absolute Value Equations: A Fixed-Time Convergence Technique. IEEE Transactions on Circuits & Systems II Express Briefs. 69(3). 1807–1811. 18 indexed citations
10.
Han, Xin, et al.. (2020). Target part detection based on improved SSD algorithm. Journal of Physics Conference Series. 1486(3). 32024–32024. 3 indexed citations
11.
Han, Xin, Rong Li, Jian Wang, Guofu Ding, & Shengfeng Qin. (2019). A systematic literature review of product platform design under uncertainty. Journal of Engineering Design. 31(5). 266–296. 29 indexed citations
12.
Han, Xin, et al.. (2019). Group topic-author model for efficient discovery of latent social astroturfing groups in tourism domain. Cybersecurity. 2(1). 3 indexed citations
13.
Li, Rong, Haizhu Zhang, Shengfeng Qin, Guofu Ding, & Xin Han. (2019). Customization design method for complex product systems based on a meta-model. Advances in Mechanical Engineering. 11(10). 387 indexed citations breakdown →
14.
Law, Rob, Gang Li, Davis Ka Chio Fong, & Xin Han. (2019). Tourism demand forecasting: A deep learning approach. Annals of Tourism Research. 75. 410–423. 307 indexed citations breakdown →
15.
Han, Xin, Rong Li, Weiyang Li, Guofu Ding, & Shengfeng Qin. (2019). User requirements dynamic elicitation of complex products from social network service. 1–6. 8 indexed citations
16.
Han, Xin, et al.. (2018). Detecting Suspicious Social Astroturfing Groups in Tourism Social Networks. 58–62. 1 indexed citations
17.
Kong, Jie, et al.. (2018). Analysis of students’ learning and psychological features by contrast frequent patterns mining on academic performance. Neural Computing and Applications. 32(1). 205–211. 12 indexed citations
18.
Han, Xin, Rong Li, Jian Wang, Shengfeng Qin, & Guofu Ding. (2017). Identification of key design characteristics for complex product adaptive design. The International Journal of Advanced Manufacturing Technology. 95(1-4). 1215–1231. 22 indexed citations
19.
Zhang, Haizhu, Xin Han, Rong Li, et al.. (2016). A new conceptual design method to support rapid and effective mapping from product design specification to concept design. The International Journal of Advanced Manufacturing Technology. 87(5-8). 2375–2389. 34 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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