Xiaochen Lai

441 total citations
26 papers, 268 citations indexed

About

Xiaochen Lai is a scholar working on Artificial Intelligence, Information Systems and Signal Processing. According to data from OpenAlex, Xiaochen Lai has authored 26 papers receiving a total of 268 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 9 papers in Information Systems and 8 papers in Signal Processing. Recurrent topics in Xiaochen Lai's work include Neural Networks and Applications (8 papers), Time Series Analysis and Forecasting (6 papers) and Data Mining Algorithms and Applications (4 papers). Xiaochen Lai is often cited by papers focused on Neural Networks and Applications (8 papers), Time Series Analysis and Forecasting (6 papers) and Data Mining Algorithms and Applications (4 papers). Xiaochen Lai collaborates with scholars based in China, Jordan and Taiwan. Xiaochen Lai's co-authors include Xin Wei, Wei Wang, Liyong Zhang, Wei Lu, Chongquan Zhong, Xin Liu, Quanli Liu, Kuei‐Fang Hsiao, Zheng Zhang and Mohammad S. Obaidat and has published in prestigious journals such as IEEE Access, Sensors and Information Sciences.

In The Last Decade

Xiaochen Lai

19 papers receiving 258 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiaochen Lai China 6 106 89 66 50 37 26 268
Xihe Qiu China 10 39 0.4× 52 0.6× 86 1.3× 28 0.6× 36 1.0× 57 305
Sérgio D. Correia Portugal 9 44 0.4× 47 0.5× 78 1.2× 45 0.9× 69 1.9× 36 281
Shili Xiang Singapore 9 36 0.3× 128 1.4× 57 0.9× 111 2.2× 33 0.9× 28 289
Élisson da Silva Rocha Brazil 9 110 1.0× 139 1.6× 70 1.1× 158 3.2× 52 1.4× 29 342
Dipanwita Thakur India 10 71 0.7× 91 1.0× 85 1.3× 188 3.8× 35 0.9× 27 324
B. Perumal India 10 28 0.3× 69 0.8× 62 0.9× 98 2.0× 42 1.1× 50 247
Xiangmao Chang China 11 78 0.7× 178 2.0× 34 0.5× 37 0.7× 151 4.1× 34 346
Pranay Yadav India 12 50 0.5× 73 0.8× 42 0.6× 62 1.2× 94 2.5× 35 355
Matteo Terzi Italy 7 25 0.2× 40 0.4× 134 2.0× 30 0.6× 32 0.9× 17 292
S. Lokesh India 7 48 0.5× 137 1.5× 90 1.4× 63 1.3× 56 1.5× 41 391

Countries citing papers authored by Xiaochen Lai

Since Specialization
Citations

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

Fields of papers citing papers by Xiaochen Lai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaochen Lai

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaochen Lai. A scholar is included among the top collaborators of Xiaochen Lai 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 Xiaochen Lai. Xiaochen Lai 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
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Lai, Xiaochen, et al.. (2025). Optical Communications in Autonomous Driving Vehicles: Requirements, Challenges, and Opportunities. Journal of Lightwave Technology. 43(4). 1690–1699. 3 indexed citations
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Lai, Xiaochen, et al.. (2025). Dynamic graph-based bilateral recurrent imputation network for multivariate time series. Neural Networks. 186. 107298–107298. 2 indexed citations
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Lai, Xiaochen, Zheng Zhang, Hui Chen, et al.. (2025). Tracking-removed neural network with graph information for classification of incomplete data. Applied Intelligence. 55(4).
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Yan, Xiaoming, et al.. (2023). Fuzzy neuron modeling of incomplete data for missing value imputation. Information Sciences. 659. 120065–120065. 4 indexed citations
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Zhang, Liyong, et al.. (2022). Image feature selection embedded distribution differences between classes for convolutional neural network. Applied Soft Computing. 131. 109715–109715. 7 indexed citations
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Lai, Xiaochen, et al.. (2022). Auto-Associative LSTM for Multivariate Time Series Imputation. 2022 41st Chinese Control Conference (CCC). 7382–7387. 3 indexed citations
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Lai, Xiaochen, et al.. (2021). Imbalanced-type Incomplete Data Fuzzy Modeling and Missing Value Imputations. 33–37. 1 indexed citations
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Lai, Xiaochen, Liyong Zhang, & Xin Liu. (2020). Takagi-Sugeno Modeling of Incomplete Data for Missing Value Imputation With the Use of Alternate Learning. IEEE Access. 8. 83633–83644. 15 indexed citations
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Lai, Xiaochen, et al.. (2020). Autoencoder-based multi-task learning for imputation and classification of incomplete data. Applied Soft Computing. 98. 106838–106838. 19 indexed citations
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Lai, Xiaochen, et al.. (2019). Imputations of missing values using a tracking-removed autoencoder trained with incomplete data. Neurocomputing. 366. 54–65. 44 indexed citations
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Lai, Xiaochen, et al.. (2019). Missing Value Imputations by Rule-Based Incomplete Data Fuzzy Modeling. 1. 1–6. 3 indexed citations
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Lai, Xiaochen, et al.. (2012). Dynamic game with perfect and complete information based dynamic channel assignment. Applied Intelligence. 39(4). 692–704. 5 indexed citations
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Lai, Xiaochen, et al.. (2010). Research on XML Based Static Software Security Analysis. 141–144. 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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