Li Xiao

2.1k total citations
95 papers, 1.4k citations indexed

About

Li Xiao is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Li Xiao has authored 95 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Cognitive Neuroscience, 21 papers in Artificial Intelligence and 18 papers in Computer Vision and Pattern Recognition. Recurrent topics in Li Xiao's work include Functional Brain Connectivity Studies (22 papers), Advanced Neuroimaging Techniques and Applications (14 papers) and Sparse and Compressive Sensing Techniques (8 papers). Li Xiao is often cited by papers focused on Functional Brain Connectivity Studies (22 papers), Advanced Neuroimaging Techniques and Applications (14 papers) and Sparse and Compressive Sensing Techniques (8 papers). Li Xiao collaborates with scholars based in China, United States and France. Li Xiao's co-authors include Xianhua Tang, Xiang‐Gen Xia, Yu‐Ping Wang, Vince D. Calhoun, Tony W. Wilson, Julia M. Stephen, Tonghai Jiang, Zhu‐Hong You, Xin Tong and Yue Dong and has published in prestigious journals such as NeuroImage, Chemical Communications and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Li Xiao

88 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Li Xiao China 21 270 250 240 189 162 95 1.4k
Lei Yuan China 18 336 1.2× 116 0.5× 90 0.4× 194 1.0× 232 1.4× 79 1.6k
Pablo Padilla Spain 25 239 0.9× 84 0.3× 144 0.6× 92 0.5× 33 0.2× 174 2.1k
Yue M. Lu United States 24 647 2.4× 118 0.5× 130 0.5× 62 0.3× 588 3.6× 90 1.9k
Facundo Mémoli United States 22 746 2.8× 113 0.5× 195 0.8× 212 1.1× 680 4.2× 67 2.2k
Ami Wiesel Israel 27 170 0.6× 73 0.3× 411 1.7× 69 0.4× 290 1.8× 87 3.8k
Yi‐Fei Pu China 28 883 3.3× 62 0.2× 88 0.4× 43 0.2× 166 1.0× 131 2.3k
Felix Abramovich Israel 13 570 2.1× 179 0.7× 42 0.2× 67 0.4× 142 0.9× 29 1.3k
Simone Fiori Italy 22 281 1.0× 46 0.2× 95 0.4× 77 0.4× 208 1.3× 172 1.8k
Naoki Saito United States 16 520 1.9× 72 0.3× 75 0.3× 36 0.2× 106 0.7× 62 1.1k

Countries citing papers authored by Li Xiao

Since Specialization
Citations

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

Fields of papers citing papers by Li Xiao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Li Xiao

This figure shows the co-authorship network connecting the top 25 collaborators of Li Xiao. A scholar is included among the top collaborators of Li 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 Li Xiao. Li Xiao 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.
Xiao, Li, et al.. (2025). Luteolin: exploring its therapeutic potential and molecular mechanisms in pulmonary diseases. Frontiers in Pharmacology. 16. 1535555–1535555. 10 indexed citations
2.
3.
Yan, Kai, Baisheng Dai, Honggui Liu, et al.. (2024). Deep neural network with adaptive dual-modality fusion for temporal aggressive behavior detection of group-housed pigs. Computers and Electronics in Agriculture. 224. 109243–109243. 10 indexed citations
4.
Wang, Wei, Li Xiao, Gang Qu, et al.. (2024). Multiview hyperedge-aware hypergraph embedding learning for multisite, multiatlas fMRI based functional connectivity network analysis. Medical Image Analysis. 94. 103144–103144. 11 indexed citations
5.
Qu, Gang, Gemeng Zhang, Li Xiao, et al.. (2023). Interpretable Cognitive Ability Prediction: A Comprehensive Gated Graph Transformer Framework for Analyzing Functional Brain Networks. IEEE Transactions on Medical Imaging. 43(4). 1568–1578. 6 indexed citations
6.
Zhang, Hongbo, et al.. (2023). Multi-step prediction of chlorophyll concentration based on adaptive graph-temporal convolutional network with series decomposition. Measurement Science and Technology. 35(3). 35801–35801. 3 indexed citations
7.
Zhang, Gemeng, Biao Cai, Aiying Zhang, et al.. (2022). Detecting abnormal connectivity in schizophrenia via a joint directed acyclic graph estimation model. NeuroImage. 260. 119451–119451. 12 indexed citations
8.
Qu, Gang, Wenxing Hu, Li Xiao, et al.. (2021). Brain Functional Connectivity Analysis via Graphical Deep Learning. IEEE Transactions on Biomedical Engineering. 69(5). 1696–1706. 20 indexed citations
9.
Qu, Gang, Li Xiao, Wenxing Hu, et al.. (2021). Ensemble Manifold Regularized Multi-Modal Graph Convolutional Network for Cognitive Ability Prediction. IEEE Transactions on Biomedical Engineering. 68(12). 3564–3573. 35 indexed citations
10.
Xiao, Li, Aiying Zhang, Biao Cai, et al.. (2020). Correlation Guided Graph Learning to Estimate Functional Connectivity Patterns From fMRI Data. IEEE Transactions on Biomedical Engineering. 68(4). 1154–1165. 8 indexed citations
11.
Qu, Qing, et al.. (2020). Geometric Analysis of Nonconvex Optimization Landscapes for Overcomplete Learning. International Conference on Learning Representations. 6 indexed citations
12.
Xiao, Li, Gemeng Zhang, Biao Cai, et al.. (2020). Multi-Paradigm fMRI Fusion via Sparse Tensor Decomposition in Brain Functional Connectivity Study. IEEE Journal of Biomedical and Health Informatics. 25(5). 1712–1723. 11 indexed citations
13.
Pan, Guixia, Li Xiao, Yuntong Bai, et al.. (2020). Multiview Diffusion Map Improves Prediction of Fluid Intelligence With Two Paradigms of fMRI Analysis. IEEE Transactions on Biomedical Engineering. 68(8). 2529–2539. 9 indexed citations
14.
Xiao, Li, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, & Yu‐Ping Wang. (2019). A Manifold Regularized Multi-Task Learning Model for IQ Prediction From Two fMRI Paradigms. IEEE Transactions on Biomedical Engineering. 67(3). 796–806. 32 indexed citations
15.
Xiao, Li, Peyman Hosseinzadeh Kassani, Yuntong Bai, et al.. (2019). Multi-Hypergraph Learning-Based Brain Functional Connectivity Analysis in fMRI Data. IEEE Transactions on Medical Imaging. 39(5). 1746–1758. 63 indexed citations
16.
Wang, Xian, Jiafei Zhang, Li Zhou, et al.. (2019). Long-term iron exposure causes widespread molecular alterations associated with memory impairment in mice. Food and Chemical Toxicology. 130. 242–252. 17 indexed citations
17.
Yi, Hai-Cheng, Zhu‐Hong You, De-Shuang Huang, et al.. (2018). A Deep Learning Framework for Robust and Accurate Prediction of ncRNA-Protein Interactions Using Evolutionary Information. Molecular Therapy — Nucleic Acids. 11. 337–344. 96 indexed citations
18.
Xiao, Li, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, & Yu‐Ping Wang. (2018). Alternating Diffusion Map Based Fusion of Multimodal Brain Connectivity Networks for IQ Prediction. IEEE Transactions on Biomedical Engineering. 66(8). 2140–2151. 20 indexed citations
19.
Wang, Yanbin, Zhu‐Hong You, Li Xiao, et al.. (2017). Predicting protein–protein interactions from protein sequences by a stacked sparse autoencoder deep neural network. Molecular BioSystems. 13(7). 1336–1344. 86 indexed citations
20.
Xiao, Li. (2002). The Definition and Recognition of Protein Structural Class. PROGRESS IN BIOCHEMISTRY AND BIOPHYSICS. 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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