Cheng Lian

1.1k total citations · 1 hit paper
52 papers, 748 citations indexed

About

Cheng Lian is a scholar working on Artificial Intelligence, Cardiology and Cardiovascular Medicine and Cognitive Neuroscience. According to data from OpenAlex, Cheng Lian has authored 52 papers receiving a total of 748 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 14 papers in Cardiology and Cardiovascular Medicine and 14 papers in Cognitive Neuroscience. Recurrent topics in Cheng Lian's work include ECG Monitoring and Analysis (14 papers), EEG and Brain-Computer Interfaces (14 papers) and Phonocardiography and Auscultation Techniques (6 papers). Cheng Lian is often cited by papers focused on ECG Monitoring and Analysis (14 papers), EEG and Brain-Computer Interfaces (14 papers) and Phonocardiography and Auscultation Techniques (6 papers). Cheng Lian collaborates with scholars based in China, Saudi Arabia and Italy. Cheng Lian's co-authors include Zhigang Zeng, Wei Yao, Huiming Tang, Bingrong Xu, Yixin Su, Junbin Zang, Zhidong Zhang, Chenyang Xue, Zhengming Ding and Xiaoping Wang and has published in prestigious journals such as IEEE Transactions on Image Processing, IEEE Transactions on Smart Grid and Pattern Recognition.

In The Last Decade

Cheng Lian

44 papers receiving 735 citations

Hit Papers

A Multi-View Multi-Scale Neural Network for Multi-Label E... 2023 2026 2024 2025 2023 25 50 75
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.

  1. A Multi-View Multi-Scale Neural Network for Multi-Label ECG Classification
    2023 75 citations Cheng Lian, Zhigang Zeng et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Cheng Lian China 15 182 151 149 140 125 52 748
Jiahao Deng China 16 129 0.7× 207 1.4× 10 0.1× 174 1.2× 150 1.2× 66 971
Yadong Liu China 15 43 0.2× 26 0.2× 15 0.1× 45 0.3× 105 0.8× 44 838
D. Mandic United Kingdom 4 55 0.3× 8 0.1× 81 0.5× 51 0.4× 87 0.7× 9 713
Ivan Štajduhar Croatia 15 255 1.4× 8 0.1× 23 0.2× 95 0.7× 33 0.3× 54 736
Rui‐Sheng Jia China 19 161 0.9× 10 0.1× 54 0.4× 449 3.2× 37 0.3× 85 1.0k
Mohamad Mahmoud Al Rahhal Saudi Arabia 20 442 2.4× 12 0.1× 439 2.9× 651 4.7× 19 0.2× 44 1.9k
Yi Zhou China 15 101 0.6× 18 0.1× 13 0.1× 375 2.7× 36 0.3× 128 1.0k
Ignasi Vilajosana Spain 15 132 0.7× 485 3.2× 9 0.1× 44 0.3× 48 0.4× 27 1.1k

Countries citing papers authored by Cheng Lian

Since Specialization
Citations

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

Fields of papers citing papers by Cheng Lian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cheng Lian

This figure shows the co-authorship network connecting the top 25 collaborators of Cheng Lian. A scholar is included among the top collaborators of Cheng Lian 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 Cheng Lian. Cheng Lian 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.
2.
Lian, Cheng, et al.. (2025). Large Language Model-assisted multi-scale hierarchical classification of ECG signals. Knowledge-Based Systems. 324. 113807–113807. 1 indexed citations
3.
Lian, Cheng, et al.. (2024). A MIL-based framework via contrastive instance learning and multimodal learning for long-term ECG classification. Applied Soft Computing. 167. 112372–112372.
4.
Xu, Bingrong, et al.. (2024). Low-Rank Optimal Transport for Robust Domain Adaptation. IEEE/CAA Journal of Automatica Sinica. 11(7). 1667–1680. 5 indexed citations
5.
Lian, Cheng, et al.. (2024). Driving Cognitive Alertness Detecting Using Evoked Multimodal Physiological Signals Based on Uncertain Self-Supervised Learning. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 32. 2165–2176. 1 indexed citations
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Lian, Cheng, et al.. (2024). Bimodal Masked Autoencoders with internal representation connections for electrocardiogram classification. Pattern Recognition. 161. 111311–111311. 1 indexed citations
8.
Lian, Cheng, Qianqian Wu, Ying Hou, et al.. (2024). Deep brain stimulation of the subthalamic nucleus increases the risk of sialorrhea in patients with advanced Parkinson's disease. Parkinsonism & Related Disorders. 123(3). 106075–106075. 1 indexed citations
9.
Zhang, Siyuan, et al.. (2024). 12-Lead ECG signal classification for detecting ECG arrhythmia via an information bottleneck-based multi-scale network. Information Sciences. 662. 120239–120239. 17 indexed citations
10.
Su, Yixin, et al.. (2024). Integrated Spatial Kinematics–Dynamics Model Predictive Control for Collision-Free Autonomous Vehicle Tracking. Actuators. 13(4). 153–153. 2 indexed citations
11.
Zhou, Jinjie, Baohui Zhang, Xilin Yuan, et al.. (2023). YOLO-CIR: The network based on YOLO and ConvNeXt for infrared object detection. Infrared Physics & Technology. 131. 104703–104703. 51 indexed citations
12.
13.
Zang, Junbin, Cheng Lian, Bingrong Xu, et al.. (2023). AmtNet: Attentional multi-scale temporal network for phonocardiogram signal classification. Biomedical Signal Processing and Control. 85. 104934–104934. 12 indexed citations
14.
Zhang, Siyuan, Cheng Lian, Bingrong Xu, Junbin Zang, & Zhigang Zeng. (2023). A token selection-based multi-scale dual-branch CNN-transformer network for 12-lead ECG signal classification. Knowledge-Based Systems. 280. 111006–111006. 18 indexed citations
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Yao, Wei, Cheng Lian, & Lorenzo Bruzzone. (2022). A CNN Ensemble Based on a Spectral Feature Refining Module for Hyperspectral Image Classification. Remote Sensing. 14(19). 4982–4982. 2 indexed citations
17.
Jiang, Hao, et al.. (2022). Multi-Modal Fusion Transformer for Multivariate Time Series Classification. 284–288. 5 indexed citations
18.
Yao, Wei, Cheng Lian, & Lorenzo Bruzzone. (2020). ClusterCNN: Clustering-Based Feature Learning for Hyperspectral Image Classification. IEEE Geoscience and Remote Sensing Letters. 18(11). 1991–1995. 18 indexed citations
19.
Zhou, Wei, Cheng Lian, Zhigang Zeng, & Yixin Su. (2019). Mutual Improvement Between Temporal Ensembling and Virtual Adversarial Training. Neural Processing Letters. 51(2). 1111–1124. 2 indexed citations
20.
Yao, Jianrong & Cheng Lian. (2016). A New Ensemble Model based Support Vector Machine for Credit Assessing. International Journal of Grid and Distributed Computing. 9(6). 159–168. 5 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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