Xiaojun Ning

538 total citations · 1 hit paper
10 papers, 365 citations indexed

About

Xiaojun Ning is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Artificial Intelligence. According to data from OpenAlex, Xiaojun Ning has authored 10 papers receiving a total of 365 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Cognitive Neuroscience, 5 papers in Experimental and Cognitive Psychology and 4 papers in Artificial Intelligence. Recurrent topics in Xiaojun Ning's work include EEG and Brain-Computer Interfaces (8 papers), Emotion and Mood Recognition (5 papers) and Sentiment Analysis and Opinion Mining (2 papers). Xiaojun Ning is often cited by papers focused on EEG and Brain-Computer Interfaces (8 papers), Emotion and Mood Recognition (5 papers) and Sentiment Analysis and Opinion Mining (2 papers). Xiaojun Ning collaborates with scholars based in China, United States and Singapore. Xiaojun Ning's co-authors include Ziyu Jia, Youfang Lin, Jing Wang, Jing Wang, Li-wei H. Lehman, Youfang Lin, Xiaoli Li, Wei Xu, Yunze Li and Xuehui Wang and has published in prestigious journals such as Neural Networks, IEEE Transactions on Instrumentation and Measurement and IEEE Transactions on Neural Systems and Rehabilitation Engineering.

In The Last Decade

Xiaojun Ning

9 papers receiving 364 citations

Hit Papers

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What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Multi-View Spatial-Temporal Graph Convolutional Networks With Domain Generalization for Sleep Stage Classification

2021 160 citations Ziyu Jia, Youfang Lin et al. IEEE Transactions on Neural Systems and Rehabilitation Engineering profile →

Peers

Countries citing papers authored by Xiaojun Ning

Since Specialization

Citations

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

Fields of papers citing papers by Xiaojun Ning

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaojun Ning

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

All Works

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10 of 10 papers shown

#	Work	Indexed citations
1	Group-wise relation mining for weakly-supervised fine-grained multimodal emotion recognition 2025 ·Neural Networks ·(unknown), Jing Wang, (unknown), Xiaojun Ning, Tao Xin, Youfang Lin	2
2	Two-Stream Dynamic Heterogeneous Graph Recurrent Neural Network for Multi-Label Multi-Modal Emotion Recognition 2025 ·IEEE Transactions on Affective Computing ·Jing Wang, (unknown), Xiaojun Ning, Youfang Lin, Badong Chen, Ziyu Jia	2
3	MoCERNet: A Modality-Complete Modeling Framework for Emotion Recognition in Physiological Signals under Imperfect Modal Matching 2025 ·(unknown), Jing Wang, (unknown), Xiaojun Ning, (unknown), Youfang Lin	0
4	Subject-Adaptation Salient Wave Detection Network for Multimodal Sleep Stage Classification 2024 ·IEEE Journal of Biomedical and Health Informatics ·Jing Wang, Xuehui Wang, Xiaojun Ning, Youfang Lin, Huy Phan, Ziyu Jia	3
5	Multi-source Selective Graph Domain Adaptation Network for cross-subject EEG emotion recognition 2024 ·Neural Networks ·Jing Wang, Xiaojun Ning, Wei Xu, Yunze Li, Ziyu Jia, Youfang Lin	12
6	Multi-View Consistency Contrastive Learning With Hard Positives for Sleep Signals 2023 ·IEEE Signal Processing Letters ·(unknown), Youfang Lin, (unknown), Xiaojun Ning, Jing Wang	1
7	A Bayesian Graph Neural Network for EEG Classification — A Win-Win on Performance and Interpretability 2023 ·Jing Wang, Xiaojun Ning, (unknown), Youfang Lin	4
8	MetaEmotionNet: Spatial–Spectral–Temporal-Based Attention 3-D Dense Network With Meta-Learning for EEG Emotion Recognition 2023 ·IEEE Transactions on Instrumentation and Measurement ·Xiaojun Ning, Jing Wang, Youfang Lin, (unknown), (unknown), (unknown), Xiaoli Li, Ziyu Jia	27
9	Multi-View Spatial-Temporal Graph Convolutional Networks With Domain Generalization for Sleep Stage Classification breakdown → 2021 ·IEEE Transactions on Neural Systems and Rehabilitation Engineering ·Ziyu Jia, Youfang Lin, Jing Wang, Xiaojun Ning, (unknown), (unknown), (unknown), Li-wei H. Lehman	160
10	GraphSleepNet: Adaptive Spatial-Temporal Graph Convolutional Networks for Sleep Stage Classification 2020 ·Ziyu Jia, Youfang Lin, Jing Wang, (unknown), Xiaojun Ning, (unknown), (unknown)	154

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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