Jun Zhou

2.1k total citations
137 papers, 1.4k citations indexed

About

Jun Zhou is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Biomedical Engineering. According to data from OpenAlex, Jun Zhou has authored 137 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Electrical and Electronic Engineering, 44 papers in Computer Vision and Pattern Recognition and 33 papers in Biomedical Engineering. Recurrent topics in Jun Zhou's work include Advanced Memory and Neural Computing (22 papers), ECG Monitoring and Analysis (19 papers) and EEG and Brain-Computer Interfaces (18 papers). Jun Zhou is often cited by papers focused on Advanced Memory and Neural Computing (22 papers), ECG Monitoring and Analysis (19 papers) and EEG and Brain-Computer Interfaces (18 papers). Jun Zhou collaborates with scholars based in China, United States and Singapore. Jun Zhou's co-authors include Guanghai Dai, Jiahui Huang, Ning Wang, Liang Chang, Yuxiang Xie, Jianbiao Xiao, Ning Wang, Qingsong Liu, Sixu Li and Shuisheng Lin and has published in prestigious journals such as Nature Communications, Journal of Applied Physics and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Jun Zhou

122 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jun Zhou China 18 491 469 406 242 235 137 1.4k
Qiang Fang Australia 22 422 0.9× 338 0.7× 690 1.7× 133 0.5× 309 1.3× 153 1.7k
Zhi Yang China 20 538 1.1× 719 1.5× 407 1.0× 330 1.4× 103 0.4× 90 1.8k
Amit M. Joshi India 20 295 0.6× 344 0.7× 502 1.2× 197 0.8× 157 0.7× 142 1.5k
Hani Saleh United Arab Emirates 23 1.0k 2.0× 172 0.4× 584 1.4× 147 0.6× 306 1.3× 155 1.8k
Sugata Munshi India 21 366 0.7× 311 0.7× 265 0.7× 221 0.9× 134 0.6× 67 1.4k
Ahmad Ayatollahi Iran 18 249 0.5× 237 0.5× 170 0.4× 288 1.2× 173 0.7× 97 1.2k
Luigi Raffo Italy 24 944 1.9× 321 0.7× 501 1.2× 160 0.7× 230 1.0× 200 2.3k
Muhammad Ibn Ibrahimy Malaysia 18 425 0.9× 449 1.0× 641 1.6× 60 0.2× 277 1.2× 132 1.4k
Ergun Erçelebi Türkiye 16 237 0.5× 410 0.9× 123 0.3× 345 1.4× 174 0.7× 69 1.4k
Julius Georgiou Cyprus 21 999 2.0× 776 1.7× 585 1.4× 61 0.3× 114 0.5× 139 2.3k

Countries citing papers authored by Jun Zhou

Since Specialization
Citations

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

Fields of papers citing papers by Jun Zhou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun Zhou

This figure shows the co-authorship network connecting the top 25 collaborators of Jun Zhou. A scholar is included among the top collaborators of Jun Zhou 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 Jun Zhou. Jun Zhou 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.
Huang, Jinfeng, et al.. (2026). ConsistentID: Portrait Generation With Multimodal Fine-Grained Identity Preserving. IEEE Transactions on Pattern Analysis and Machine Intelligence. PP. 1–17.
2.
Lu, Yuncheng, Jinhong Guo, Liang Zhou, et al.. (2025). FSNAP: An Ultra-Energy-Efficient Reconfigurable Few-Spikes-Neuron-Based SNN Processor Supporting Unified On-Chip Learning and Adaptive Time-Window Tuning. IEEE Journal of Solid-State Circuits. 61(2). 791–807.
3.
Liu, Jiaming, et al.. (2025). Nighttime Glare Removal for Consumer Electronics via Latent Space Transformation and Feature-Enhanced Attention Mechanism. IEEE Transactions on Consumer Electronics. 71(2). 6719–6733.
4.
Liu, Hanlin, Xiangpeng Xiao, Jun Zhou, et al.. (2025). Fibertouch: A novel fiber-optic tactile sensor with deep learning demodulation for dexterous robotic hands. Mechanical Systems and Signal Processing. 238. 113212–113212. 1 indexed citations
5.
Zhou, Jun, et al.. (2024). A recommendation model of rice fertilization using knowledge graph and case-based reasoning. Computers and Electronics in Agriculture. 219. 108751–108751. 9 indexed citations
6.
Liu, Ye, Shuang Hao, Kun Huang, et al.. (2024). An FPGA-based Ultra-High Performance and Scalable Optical Flow Hardware Accelerator for Autonomous Driving. 1–5. 2 indexed citations
7.
8.
9.
Liu, Jiahao, et al.. (2023). Transposable 9T-SRAM Computation-In-Memory for on-Chip Learning With Probability-Based Single-Slope SAR Hybrid ADC for Edge Devices. IEEE Solid-State Circuits Letters. 6. 81–84. 4 indexed citations
10.
Chang, Liang, et al.. (2023). General Purpose Deep Learning Accelerator Based on Bit Interleaving. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 43(5). 1470–1483. 5 indexed citations
11.
Zhao, Ying, et al.. (2023). Development of Flexible Electronic Biosensors for Healthcare Engineering. IEEE Sensors Journal. 24(8). 11998–12016. 17 indexed citations
12.
Liu, Xiyuan, Jingxiao Zheng, Teng Zhang, et al.. (2023). An Energy-Efficient Visual Object Tracking Processor Exploiting Domain-Specific Features. IEEE Transactions on Circuits & Systems II Express Briefs. 71(5). 2794–2798. 1 indexed citations
13.
Xue, Ning, Siyuan Yin, Yi Shi, et al.. (2022). Multi-Dimensional Feature Combination Method for Continuous Blood Pressure Measurement Based on Wrist PPG Sensor. IEEE Journal of Biomedical and Health Informatics. 26(8). 3708–3719. 23 indexed citations
14.
Li, Sixu, Jianbiao Xiao, Jiahao Liu, et al.. (2022). An Ultra-Energy-Efficient and High Accuracy ECG Classification Processor With SNN Inference Assisted by On-Chip ANN Learning. IEEE Transactions on Biomedical Circuits and Systems. 16(5). 832–841. 29 indexed citations
15.
Zhang, Teng, Qingsong Liu, Jiahui Huang, et al.. (2022). An Energy-Efficient Reconfigurable AI-Based Object Detection and Tracking Processor Supporting Online Object Learning. IEEE Solid-State Circuits Letters. 5. 78–81. 4 indexed citations
16.
Liu, Jiahao, Zhen Zhu, Yong Zhou, et al.. (2021). 4.5 BioAIP: A Reconfigurable Biomedical AI Processor with Adaptive Learning for Versatile Intelligent Health Monitoring. 62–64. 74 indexed citations
17.
Yin, Siyuan, Ning Xue, Yi Shi, et al.. (2021). Wearable Physiological Multi-Vital Sign Monitoring System With Medical Standard. IEEE Sensors Journal. 21(23). 27157–27167. 13 indexed citations
18.
Guo, Zhiming, et al.. (2020). Watercore Identification of Xinjiang Fuji Apple Based on Manifold Learning Algorithm and Near Infrared Transmission Spectroscopy. Guangpuxue yu guangpu fenxi. 40(8). 2415. 3 indexed citations
19.
Zhou, Jun. (2013). Parallel Go on CUDA with Monte Carlo Tree Search. OhioLink ETD Center (Ohio Library and Information Network). 1 indexed citations
20.
Zhong, Renbin, Weihao Liu, Jun Zhou, & Shenggang Liu. (2012). Surface plasmon wave propagation along single metal wire. Chinese Physics B. 21(11). 117303–117303. 17 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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