Zhaofei Yu

3.5k total citations · 2 hit papers
98 papers, 1.9k citations indexed

About

Zhaofei Yu is a scholar working on Electrical and Electronic Engineering, Cognitive Neuroscience and Artificial Intelligence. According to data from OpenAlex, Zhaofei Yu has authored 98 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Electrical and Electronic Engineering, 43 papers in Cognitive Neuroscience and 27 papers in Artificial Intelligence. Recurrent topics in Zhaofei Yu's work include Neural dynamics and brain function (41 papers), Advanced Memory and Neural Computing (40 papers) and CCD and CMOS Imaging Sensors (14 papers). Zhaofei Yu is often cited by papers focused on Neural dynamics and brain function (41 papers), Advanced Memory and Neural Computing (40 papers) and CCD and CMOS Imaging Sensors (14 papers). Zhaofei Yu collaborates with scholars based in China, United Kingdom and United States. Zhaofei Yu's co-authors include Tiejun Huang, Yonghong Tian, Timothée Masquelier, Yanqi Chen, Penglin Dai, Jianhao Ding, Huanlai Xing, Wei Fang, Xiao Wu and Jian K. Liu and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Zhaofei Yu

86 papers receiving 1.9k citations

Hit Papers

Incorporating Learnable Membrane Time Constant to Enhance... 2021 2026 2022 2024 2021 2023 100 200 300
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. Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks
    2021 356 citations Zhaofei Yu, Yanqi Chen et al. profile →
  2. SpikingJelly: An open-source machine learning infrastructure platform for spike-based intelligence
    2023 159 citations Wei Fang, Yanqi Chen et al. Science Advances profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhaofei Yu China 23 1.1k 689 511 342 268 98 1.9k
Gregory Cohen Australia 14 899 0.8× 498 0.7× 923 1.8× 109 0.3× 351 1.3× 39 1.9k
Tinoosh Mohsenin United States 26 1.5k 1.3× 494 0.7× 652 1.3× 730 2.1× 495 1.8× 146 2.9k
Jonathan Tapson Australia 22 997 0.9× 678 1.0× 1.0k 2.0× 117 0.3× 335 1.3× 118 2.4k
Yang Yi United States 26 1.7k 1.5× 337 0.5× 857 1.7× 794 2.3× 74 0.3× 147 2.3k
Il Memming Park United States 23 421 0.4× 658 1.0× 475 0.9× 268 0.8× 226 0.8× 78 2.1k
Davide Rossi Italy 27 1.6k 1.4× 203 0.3× 547 1.1× 875 2.6× 559 2.1× 204 2.9k
Yufei Ding United States 23 832 0.7× 213 0.3× 1.1k 2.2× 268 0.8× 361 1.3× 106 2.0k
Zhengya Zhang United States 29 2.9k 2.5× 349 0.5× 583 1.1× 1.1k 3.3× 279 1.0× 131 3.6k
Cong Xu China 19 2.2k 1.9× 263 0.4× 724 1.4× 558 1.6× 658 2.5× 47 3.0k
Aimin Jiang China 21 331 0.3× 454 0.7× 200 0.4× 139 0.4× 366 1.4× 128 1.7k

Countries citing papers authored by Zhaofei Yu

Since Specialization
Citations

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

Fields of papers citing papers by Zhaofei Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhaofei Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Zhaofei Yu. A scholar is included among the top collaborators of Zhaofei Yu 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 Zhaofei Yu. Zhaofei Yu 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.
Xiong, Ruiqin, et al.. (2025). Self-Supervised Learning for Color Spike Camera Reconstruction. 6231–6240.
2.
Tang, Yuanhong, Shanshan Jia, Tiejun Huang, Zhaofei Yu, & Jian K. Liu. (2025). Implementing feature binding through dendritic networks of a single neuron. Neural Networks. 189. 107555–107555. 1 indexed citations
3.
Ding, Jianhao, Zhaofei Yu, Tiejun Huang, & Jian K. Liu. (2024). Enhancing the Robustness of Spiking Neural Networks with Stochastic Gating Mechanisms. Proceedings of the AAAI Conference on Artificial Intelligence. 38(1). 492–502. 5 indexed citations
4.
Hrabec, Aleš, Jianhao Ding, Peipei Ge, et al.. (2024). Ultrafast Probabilistic Neuron in an Artificial Spin Ice for Robust Deep Neural Networks. Advanced Functional Materials. 35(11). 2 indexed citations
5.
Zhang, Shiliang, et al.. (2024). Recognizing Ultra-High-Speed Moving Objects with Bio-Inspired Spike Camera. Proceedings of the AAAI Conference on Artificial Intelligence. 38(7). 7478–7486. 1 indexed citations
6.
Zhang, Xinyu, Jing Lian, Zhaofei Yu, et al.. (2024). Revealing the mechanisms of semantic satiation with deep learning models. Communications Biology. 7(1). 487–487. 4 indexed citations
7.
Jia, Shanshan, et al.. (2024). Decoding dynamic visual scenes across the brain hierarchy. PLoS Computational Biology. 20(8). e1012297–e1012297. 2 indexed citations
8.
Fang, Wei, Yanqi Chen, Jianhao Ding, et al.. (2023). SpikingJelly: An open-source machine learning infrastructure platform for spike-based intelligence. Science Advances. 9(40). eadi1480–eadi1480. 159 indexed citations breakdown →
9.
Chen, Shiyan, Zhaofei Yu, & Tiejun Huang. (2023). Self-Supervised Joint Dynamic Scene Reconstruction and Optical Flow Estimation for Spiking Camera. Proceedings of the AAAI Conference on Artificial Intelligence. 37(1). 350–358. 7 indexed citations
10.
Jia, Shanshan, et al.. (2022). Representing the dynamics of high-dimensional data with non-redundant wavelets. Patterns. 3(3). 100424–100424. 4 indexed citations
11.
Huang, Tiejun, Zhaofei Yu, Boxin Shi, et al.. (2022). Advances in spike vision. Journal of Image and Graphics. 27(6). 1823–1839. 2 indexed citations
12.
Huang, Keke, Shuo Li, Wenfeng Deng, Zhaofei Yu, & Лей Ма. (2021). Structure inference of networked system with the synergy of deep residual network and fully connected layer network. Neural Networks. 145. 288–299. 17 indexed citations
13.
Jia, Shanshan, et al.. (2021). Unraveling neural coding of dynamic natural visual scenes via convolutional recurrent neural networks. Patterns. 2(10). 100350–100350. 20 indexed citations
14.
Jia, Shanshan, Dajun Xing, Zhaofei Yu, & Jian K. Liu. (2021). Dissecting cascade computational components in spiking neural networks. PLoS Computational Biology. 17(11). e1009640–e1009640. 3 indexed citations
15.
Huang, Keke, Shuo Li, Penglin Dai, Zhen Wang, & Zhaofei Yu. (2020). SDARE: A stacked denoising autoencoder method for game dynamics network structure reconstruction. Neural Networks. 126. 143–152. 23 indexed citations
16.
An, Lingling, Doudou Wang, Shanshan Jia, et al.. (2020). Intrinsic and Synaptic Properties Shaping Diverse Behaviors of Neural Dynamics. Frontiers in Computational Neuroscience. 14. 26–26. 7 indexed citations
17.
Li, Jianing, Siwei Dong, Zhaofei Yu, Yonghong Tian, & Tiejun Huang. (2019). Event-Based Vision Enhanced: A Joint Detection Framework in Autonomous Driving. 1396–1401. 50 indexed citations
18.
Fang, Ying, et al.. (2019). Noise helps optimization escape from saddle points in the neural dynamics.. The European Symposium on Artificial Neural Networks. 1 indexed citations
19.
Yu, Zhaofei, et al.. (2017). Neural network implementation of inference on binary Markov random fields with probability coding. Applied Mathematics and Computation. 301. 193–200. 6 indexed citations
20.
Yu, Zhaofei, et al.. (2010). A Table Retrieval Algorithm Based on the Vector Space Model. Shuju fenxi yu zhishi faxian. 26(4). 41–45.

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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