Zhenyu Liu

1.1k total citations
44 papers, 510 citations indexed

About

Zhenyu Liu is a scholar working on Experimental and Cognitive Psychology, Social Psychology and Cognitive Neuroscience. According to data from OpenAlex, Zhenyu Liu has authored 44 papers receiving a total of 510 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Experimental and Cognitive Psychology, 12 papers in Social Psychology and 10 papers in Cognitive Neuroscience. Recurrent topics in Zhenyu Liu's work include Emotion and Mood Recognition (30 papers), Mental Health via Writing (12 papers) and Mental Health Research Topics (8 papers). Zhenyu Liu is often cited by papers focused on Emotion and Mood Recognition (30 papers), Mental Health via Writing (12 papers) and Mental Health Research Topics (8 papers). Zhenyu Liu collaborates with scholars based in China, United Kingdom and United States. Zhenyu Liu's co-authors include Bin Hu, Haihua Jiang, Xiaoyü Li, Fei Liu, Tianyang Wang, Hanshu Cai, Hongwu Yang, Yutong Li, Yaping Xu and Lan Zhang and has published in prestigious journals such as Journal of Cleaner Production, Marine Pollution Bulletin and IEEE Transactions on Fuzzy Systems.

In The Last Decade

Zhenyu Liu

40 papers receiving 494 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhenyu Liu China 11 315 166 103 90 84 44 510
Zhaocheng Huang Australia 13 293 0.9× 122 0.7× 162 1.6× 45 0.5× 50 0.6× 23 403
Petter Jakobsen Norway 8 239 0.8× 53 0.3× 80 0.8× 117 1.3× 164 2.0× 19 471
Kun-Yi Huang Taiwan 10 210 0.7× 65 0.4× 185 1.8× 56 0.6× 45 0.5× 25 420
Brian Stasak Australia 11 204 0.6× 98 0.6× 105 1.0× 27 0.3× 34 0.4× 14 296
Marilyn K. Silverman United States 5 378 1.2× 136 0.8× 159 1.5× 87 1.0× 65 0.8× 8 583
Stephen E. Silverman United States 5 381 1.2× 137 0.8× 159 1.5× 88 1.0× 67 0.8× 8 582
Pooya Khorrami United States 5 390 1.2× 113 0.7× 117 1.1× 75 0.8× 35 0.4× 13 502
Timur Almaev United Kingdom 7 559 1.8× 140 0.8× 166 1.6× 117 1.3× 42 0.5× 7 767
Colleen Richey United States 16 198 0.6× 90 0.5× 511 5.0× 105 1.2× 26 0.3× 35 797
Huijun Zhang China 14 151 0.5× 221 1.3× 117 1.1× 139 1.5× 110 1.3× 48 556

Countries citing papers authored by Zhenyu Liu

Since Specialization
Citations

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

Fields of papers citing papers by Zhenyu Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhenyu Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Zhenyu Liu. A scholar is included among the top collaborators of Zhenyu Liu 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 Zhenyu Liu. Zhenyu Liu 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.
Liu, Zhenyu, et al.. (2025). Corporate innovation and ESG performance: The role of government subsidies. Journal of Cleaner Production. 498. 145209–145209. 9 indexed citations
2.
Liu, Zhenyu, Bailin Chen, Yang Wu, et al.. (2025). MPDRM: A Multi-Scale Personalized Depression Recognition Model via facial movements. Neurocomputing. 632. 129669–129669.
3.
Guan, Bin, Qi Lu, Junyu Chen, et al.. (2025). FLOT1 Is a Novel Serum Biomarker of Ovarian Cancer Targeted by N6‐methyladenosine Modification Inhibition. Cell Biology International. 49(6). 674–691. 3 indexed citations
4.
Du, Siyao, Gao Si, Huidong Wang, et al.. (2025). Early prediction of neoadjuvant therapy response in breast cancer using MRI-based neural networks: data from the ACRIN 6698 trial and a prospective Chinese cohort. Breast Cancer Research. 27(1). 52–52. 2 indexed citations
5.
Liu, Zhenyu, Bailin Chen, Hanshu Cai, et al.. (2024). PIE: A Personalized Information Embedded model for text-based depression detection. Information Processing & Management. 61(6). 103830–103830. 4 indexed citations
6.
Liu, Zhenyu, et al.. (2024). Multi Fine-Grained Fusion Network for Depression Detection. ACM Transactions on Multimedia Computing Communications and Applications. 20(8). 1–23. 2 indexed citations
7.
Liu, Zhenyu, et al.. (2024). Stimulus-Response Pattern: The Core of Robust Cross-Stimulus Facial Depression Recognition. IEEE Transactions on Affective Computing. 16(2). 1146–1158. 2 indexed citations
8.
Yuan, Yongna, et al.. (2024). CKG-IMC: An inductive matrix completion method enhanced by CKG and GNN for Alzheimer’s disease compound-protein interactions prediction. Computers in Biology and Medicine. 177. 108612–108612. 1 indexed citations
9.
Liu, Zhenyu, et al.. (2023). CAIINET: Neural network based on contextual attention and information interaction mechanism for depression detection. Digital Signal Processing. 137. 103986–103986. 8 indexed citations
10.
Liu, Zhenyu, Qiongqiong Chen, Gang Li, et al.. (2023). Depression recognition base on acoustic speech model of Multi-task emotional stimulus. Biomedical Signal Processing and Control. 85. 104970–104970. 5 indexed citations
11.
Li, Yutong, et al.. (2023). A facial depression recognition method based on hybrid multi-head cross attention network. Frontiers in Neuroscience. 17. 1188434–1188434. 9 indexed citations
12.
Su, Rui, Rui Guo, Zhenyu Liu, Yongna Yuan, & Wenya Zhang. (2023). Heavy metal pollution alters reproductive performance and mate choice in an anuran, Strauchbufo raddei. Marine Pollution Bulletin. 196. 115675–115675. 2 indexed citations
13.
Hu, Jun, et al.. (2023). The Effects of Happy and Sad Dynamic Digital Art on Relieving Stress. AHFE international. 1 indexed citations
14.
Liu, Zhenyu, et al.. (2023). PRA-Net: Part-and-Relation Attention Network for depression recognition from facial expression. Computers in Biology and Medicine. 157. 106589–106589. 35 indexed citations
15.
Liu, Zhenyu, Huimin Yu, Gang Li, et al.. (2023). Ensemble learning with speaker embeddings in multiple speech task stimuli for depression detection. Frontiers in Neuroscience. 17. 1141621–1141621. 7 indexed citations
16.
Yang, Hongwu, et al.. (2021). Deep Neural Networks for Depression Recognition Based on 2D and 3D Facial Expressions Under Emotional Stimulus Tasks. Frontiers in Neuroscience. 15. 609760–609760. 46 indexed citations
17.
Yang, Hongwu, et al.. (2019). Deep Neural Networks for Depression Recognition Based on Facial Expressions Caused by Stimulus Tasks. Lanzhou University Institutional Repository. 133–139. 5 indexed citations
18.
Li, Jinlong, et al.. (2018). A novel study for MDD detection through task-elicited facial cues. Lanzhou University Institutional Repository. 1003–1008. 6 indexed citations
19.
Jiang, Haihua, Bin Hu, Zhenyu Liu, et al.. (2018). Detecting Depression Using an Ensemble Logistic Regression Model Based on Multiple Speech Features. Computational and Mathematical Methods in Medicine. 2018. 1–9. 65 indexed citations
20.
Jia, Junxiong, et al.. (2015). Prediction of protein-protein interactions using chaos game representation and wavelet transform via the random forest algorithm. Genetics and Molecular Research. 14(4). 11791–11805. 2 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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