Xiaoling Luo

617 total citations
23 papers, 354 citations indexed

About

Xiaoling Luo is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Electrical and Electronic Engineering. According to data from OpenAlex, Xiaoling Luo has authored 23 papers receiving a total of 354 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 7 papers in Cognitive Neuroscience and 7 papers in Electrical and Electronic Engineering. Recurrent topics in Xiaoling Luo's work include Neural dynamics and brain function (7 papers), Advanced Memory and Neural Computing (7 papers) and Retinal Diseases and Treatments (4 papers). Xiaoling Luo is often cited by papers focused on Neural dynamics and brain function (7 papers), Advanced Memory and Neural Computing (7 papers) and Retinal Diseases and Treatments (4 papers). Xiaoling Luo collaborates with scholars based in China, Singapore and United Kingdom. Xiaoling Luo's co-authors include Chengliang Liu, Yong Xu, Jie Wen, Lin Zuo, Lei Zhang, Zhihao Wu, Zhehan Zhang, Yu Liu, Malu Zhang and Hong Qu and has published in prestigious journals such as International Journal of Molecular Sciences, Materials Today and Pattern Recognition.

In The Last Decade

Xiaoling Luo

19 papers receiving 348 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Xiaoling Luo China	11	159	110	92	88	71	23	354
Mokhtar Nibouche United Kingdom	9	86 0.5×	142 1.3×	102 1.1×	91 1.0×	61 0.9×	55	389
Iren Valova United States	11	161 1.0×	63 0.6×	81 0.9×	39 0.4×	16 0.2×	62	333
Benoît Miramond France	11	127 0.8×	248 2.3×	94 1.0×	100 1.1×	18 0.3×	39	436
Bernard Girau France	9	200 1.3×	240 2.2×	68 0.7×	128 1.5×	45 0.6×	62	448
Hanlin Chen China	10	78 0.5×	25 0.2×	111 1.2×	45 0.5×	32 0.5×	58	336
Jonas Degrave Belgium	8	147 0.9×	57 0.5×	75 0.8×	56 0.6×	72 1.0×	16	309
Huaxiang Lu China	10	82 0.5×	72 0.7×	154 1.7×	21 0.2×	24 0.3×	69	361
Mohamed Taher Egypt	10	48 0.3×	61 0.6×	79 0.9×	57 0.6×	33 0.5×	75	355
Fengyuan Zhu Hong Kong	7	56 0.4×	60 0.5×	255 2.8×	117 1.3×	56 0.8×	11	482

Countries citing papers authored by Xiaoling Luo

Since Specialization

Citations

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

Fields of papers citing papers by Xiaoling Luo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaoling Luo

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

Luo, Xiaoling, Zhihao Wu, Chenliang Liu, et al.. (2025). Multi-view diabetic retinopathy grading via cross-view spatial alignment and adaptive vessel reinforcing. Pattern Recognition. 164. 111487–111487. 3 indexed citations

Hou, Mengshu, et al.. (2025). Spike-VAD: Efficient and Robust Spiking Neural Network for Voice Activity Detection. IEEE Transactions on Cognitive and Developmental Systems. 18(1). 89–101.

Wang, Yansong, et al.. (2025). GTPLM-GO: Enhancing Protein Function Prediction Through Dual-Branch Graph Transformer and Protein Language Model Fusing Sequence and Local–Global PPI Information. International Journal of Molecular Sciences. 26(9). 4088–4088.

Luo, Xiaoling, et al.. (2025). Enhancing Multimodal Protein Function Prediction Through Dual-Branch Dynamic Selection with Reconstructive Pre-Training. 7598–7606. 1 indexed citations

Zhang, Minmin, Dan Liu, Jingtao Li, et al.. (2025). Nucleic acid/cyanine composite nanomedicine for targeted remote tumor therapy to counteract RT-induced immunosuppression. Materials Today. 88. 272–283. 1 indexed citations

Zhang, Malu, et al.. (2024). A universal ANN-to-SNN framework for achieving high accuracy and low latency deep Spiking Neural Networks. Neural Networks. 174. 106244–106244. 11 indexed citations

Luo, Xiaoling, et al.. (2024). A Lesion-Fusion Neural Network for Multi-View Diabetic Retinopathy Grading. IEEE Journal of Biomedical and Health Informatics. 29(5). 3184–3193.

Liu, Chengliang, et al.. (2024). Attention-Induced Embedding Imputation for Incomplete Multi-View Partial Multi-Label Classification. Proceedings of the AAAI Conference on Artificial Intelligence. 38(12). 13864–13872. 13 indexed citations

Luo, Xiaoling, et al.. (2024). HACDR-Net: Heterogeneous-Aware Convolutional Network for Diabetic Retinopathy Multi-Lesion Segmentation. Proceedings of the AAAI Conference on Artificial Intelligence. 38(6). 6342–6350. 2 indexed citations

10.

Luo, Xiaoling, et al.. (2024). Spike-VisNet: A novel framework for visual recognition with FocusLayer-STDP learning. Neural Networks. 182. 106918–106918.

11.

Luo, Xiaoling, et al.. (2024). A comprehensive review and comparison of existing computational methods for protein function prediction. Briefings in Bioinformatics. 25(4). 11 indexed citations

12.

Liu, Chengliang, et al.. (2023). DICNet: Deep Instance-Level Contrastive Network for Double Incomplete Multi-View Multi-Label Classification. Proceedings of the AAAI Conference on Artificial Intelligence. 37(7). 8807–8815. 37 indexed citations

13.

Zhang, Ya, et al.. (2023). A biologically inspired auto-associative network with sparse temporal population coding. Neural Networks. 166. 670–682. 3 indexed citations

14.

Liu, Chengliang, Jie Wen, Xiaoling Luo, & Yong Xu. (2023). Incomplete Multi-View Multi-Label Learning via Label-Guided Masked View- and Category-Aware Transformers. Proceedings of the AAAI Conference on Artificial Intelligence. 37(7). 8816–8824. 37 indexed citations

15.

Liu, Chengliang, Jie Wen, Zhihao Wu, et al.. (2023). Information Recovery-Driven Deep Incomplete Multiview Clustering Network. IEEE Transactions on Neural Networks and Learning Systems. 35(11). 15442–15452. 55 indexed citations

16.

Zhang, Yun, et al.. (2021). A new recursive least squares-based learning algorithm for spiking neurons. Neural Networks. 138. 110–125. 10 indexed citations

17.

Wang, Yuchen, Xiaobin Wang, Hong Qu, et al.. (2021). Bio-inspired Model Based on Global-Local Hybrid Learning in Spiking Neural Network. 10. 1–8. 1 indexed citations

18.

Luo, Xiaoling, Hong Qu, Yun Zhang, & Yi Chen. (2019). First Error-Based Supervised Learning Algorithm for Spiking Neural Networks. Frontiers in Neuroscience. 13. 559–559. 16 indexed citations

19.

Zhang, Malu, Jibin Wu, Yansong Chua, et al.. (2019). MPD-AL: An Efficient Membrane Potential Driven Aggregate-Label Learning Algorithm for Spiking Neurons. Proceedings of the AAAI Conference on Artificial Intelligence. 33(1). 1327–1334. 36 indexed citations

20.

Luo, Xiaoling, et al.. (2013). Temperature and Humidity Acquisition System Based on Sensor DHT11. Computer and Modernization. 1(11). 133. 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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