Xia-an Bi

1.1k total citations
51 papers, 727 citations indexed

About

Xia-an Bi is a scholar working on Cognitive Neuroscience, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Xia-an Bi has authored 51 papers receiving a total of 727 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Cognitive Neuroscience, 14 papers in Molecular Biology and 13 papers in Artificial Intelligence. Recurrent topics in Xia-an Bi's work include Functional Brain Connectivity Studies (15 papers), Bioinformatics and Genomic Networks (9 papers) and Network Security and Intrusion Detection (8 papers). Xia-an Bi is often cited by papers focused on Functional Brain Connectivity Studies (15 papers), Bioinformatics and Genomic Networks (9 papers) and Network Security and Intrusion Detection (8 papers). Xia-an Bi collaborates with scholars based in China, United States and Canada. Xia-an Bi's co-authors include Qi Sun, Qian Xu, Yang Wang, Yingchao Liu, Yiming Xie, Yang Wang, Lou Li, Sheng Luo, Zhigang Wang and Qinghua Jiang and has published in prestigious journals such as Bioinformatics, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Xia-an Bi

46 papers receiving 714 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xia-an Bi China 16 343 143 142 140 122 51 727
Vasileios C. Pezoulas Greece 13 432 1.3× 58 0.4× 161 1.1× 134 1.0× 89 0.7× 71 968
Elaheh Moradi Finland 7 264 0.8× 246 1.7× 191 1.3× 370 2.6× 128 1.0× 13 810
Xiaoli Liu China 17 93 0.3× 133 0.9× 135 1.0× 159 1.1× 117 1.0× 52 613
Xiaoke Hao China 16 202 0.6× 167 1.2× 163 1.1× 135 1.0× 111 0.9× 45 811
Sofia Ira Ktena United Kingdom 11 687 2.0× 111 0.8× 274 1.9× 136 1.0× 344 2.8× 19 1.1k
Alexandre Savio Spain 15 268 0.8× 153 1.1× 158 1.1× 116 0.8× 198 1.6× 19 647
Junhao Wen United States 11 196 0.6× 301 2.1× 268 1.9× 311 2.2× 164 1.3× 30 883
Alexandre Routier France 10 156 0.5× 281 2.0× 251 1.8× 272 1.9× 155 1.3× 15 725
Chris Hinrichs United States 8 188 0.5× 224 1.6× 153 1.1× 315 2.3× 189 1.5× 11 717
Da Ma Canada 18 94 0.3× 113 0.8× 150 1.1× 125 0.9× 312 2.6× 70 900

Countries citing papers authored by Xia-an Bi

Since Specialization
Citations

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

Fields of papers citing papers by Xia-an Bi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xia-an Bi. 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 Xia-an Bi. The network helps show where Xia-an Bi may publish in the future.

Co-authorship network of co-authors of Xia-an Bi

This figure shows the co-authorship network connecting the top 25 collaborators of Xia-an Bi. A scholar is included among the top collaborators of Xia-an Bi 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 Xia-an Bi. Xia-an Bi 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.
Bi, Xia-an, et al.. (2025). MSAFF: Multi-Way Soft Attention Fusion Framework With the Large Foundation Models for the Diagnosis of Alzheimer’s Disease. IEEE Transactions on Neural Networks and Learning Systems. 36(10). 17541–17555. 1 indexed citations
2.
Wang, Qiong, et al.. (2025). CPST-GAN: Conditional Probabilistic State Transition Generative Adversarial Network With the Biomedical Large Foundation Models. IEEE Transactions on Neural Networks and Learning Systems. 36(10). 17650–17663. 1 indexed citations
3.
Bi, Xia-an, et al.. (2025). Alzheimer’s Disease Risk Prediction and Pathogeny Extraction Using Fuzzy Graph Evolutionary Generative Adversarial Network. IEEE Transactions on Neural Networks and Learning Systems. PP. 1–15.
4.
Zhang, Dafang, et al.. (2024). Bilinear Perceptual Fusion Algorithm Based on Brain Functional and Structural Data for ASD Diagnosis and Regions of Interest Identification. Interdisciplinary Sciences Computational Life Sciences. 16(4). 936–950. 2 indexed citations
5.
Chen, Jie, et al.. (2024). Deep Canonical Correlation Fusion Algorithm Based on Denoising Autoencoder for ASD Diagnosis and Pathogenic Brain Region Identification. Interdisciplinary Sciences Computational Life Sciences. 16(2). 455–468. 2 indexed citations
6.
Bi, Xia-an, et al.. (2023). Explainable and programmable hypergraph convolutional network for imaging genetics data fusion. Information Fusion. 100. 101950–101950. 16 indexed citations
7.
Bi, Xia-an, et al.. (2023). Community Graph Convolution Neural Network for Alzheimer’s Disease Classification and Pathogenetic Factors Identification. IEEE Transactions on Neural Networks and Learning Systems. 36(2). 1959–1973. 13 indexed citations
8.
9.
Bi, Xia-an, et al.. (2021). Identification of differential brain regions in MCI progression via clustering-evolutionary weighted SVM ensemble algorithm. Frontiers of Computer Science. 15(6). 17 indexed citations
10.
Bi, Xia-an, et al.. (2020). The exploration of Parkinson’s disease: a multi-modal data analysis of resting functional magnetic resonance imaging and gene data. Brain Imaging and Behavior. 15(4). 1986–1996. 10 indexed citations
11.
Bi, Xia-an, et al.. (2020). A novel CERNNE approach for predicting Parkinson’s Disease-associated genes and brain regions based on multimodal imaging genetics data. Medical Image Analysis. 67. 101830–101830. 39 indexed citations
12.
Bi, Xia-an, et al.. (2019). Effective Diagnosis of Alzheimer’s Disease via Multimodal Fusion Analysis Framework. Frontiers in Genetics. 10. 976–976. 15 indexed citations
13.
Bi, Xia-an, et al.. (2018). Analysis of Asperger Syndrome Using Genetic-Evolutionary Random Support Vector Machine Cluster. Frontiers in Physiology. 9. 1646–1646. 9 indexed citations
14.
Bi, Xia-an, et al.. (2018). The Diagnosis of Autism Spectrum Disorder Based on the Random Neural Network Cluster. Frontiers in Human Neuroscience. 12. 257–257. 29 indexed citations
15.
Bi, Xia-an, et al.. (2018). Analysis of Alzheimer’s Disease Based on the Random Neural Network Cluster in fMRI. Frontiers in Neuroinformatics. 12. 60–60. 34 indexed citations
16.
Bi, Xia-an, et al.. (2018). Abnormal Functional Connectivity of Resting State Network Detection Based on Linear ICA Analysis in Autism Spectrum Disorder. Frontiers in Physiology. 9. 475–475. 39 indexed citations
17.
Bi, Xia-an, et al.. (2018). Classification of Autism Spectrum Disorder Using Random Support Vector Machine Cluster. Frontiers in Genetics. 9. 18–18. 106 indexed citations
18.
Bi, Xia-an, et al.. (2018). Random support vector machine cluster analysis of resting-state fMRI in Alzheimer's disease. PLoS ONE. 13(3). e0194479–e0194479. 51 indexed citations
19.
Bi, Xia-an, et al.. (2018). Weighted Random Support Vector Machine Clusters Analysis of Resting-State fMRI in Mild Cognitive Impairment. Frontiers in Psychiatry. 9. 340–340. 9 indexed citations
20.
Bi, Xia-an, et al.. (2017). Hierarchical trie packet classification algorithm based on expectation-maximization clustering. PLoS ONE. 12(7). e0181049–e0181049. 1 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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