Man Yao

734 total citations · 2 hit papers
15 papers, 366 citations indexed

About

Man Yao is a scholar working on Electrical and Electronic Engineering, Cognitive Neuroscience and Cellular and Molecular Neuroscience. According to data from OpenAlex, Man Yao has authored 15 papers receiving a total of 366 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Electrical and Electronic Engineering, 7 papers in Cognitive Neuroscience and 4 papers in Cellular and Molecular Neuroscience. Recurrent topics in Man Yao's work include Advanced Memory and Neural Computing (11 papers), Neural dynamics and brain function (6 papers) and Ferroelectric and Negative Capacitance Devices (6 papers). Man Yao is often cited by papers focused on Advanced Memory and Neural Computing (11 papers), Neural dynamics and brain function (6 papers) and Ferroelectric and Negative Capacitance Devices (6 papers). Man Yao collaborates with scholars based in China, Hong Kong and Austria. Man Yao's co-authors include Guoqi Li, Guangshe Zhao, Lei Deng, Yifan Hu, Dingheng Wang, Yonghong Tian, Bo Xu, Yihan Lin, Zhao-Xu Yang and Yujie Wu and has published in prestigious journals such as Nature Communications, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Neural Networks and Learning Systems.

In The Last Decade

Man Yao

10 papers receiving 356 citations

Hit Papers

Attention Spiking Neural Networks 2023 2026 2024 2025 2023 2024 40 80 120
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. Attention Spiking Neural Networks
    2023 122 citations Man Yao, Guangshe Zhao et al. IEEE Transactions on Pattern Analysis and Machine Intelligence profile →
  2. Advancing Spiking Neural Networks Toward Deep Residual Learning
    2024 55 citations Yifan Hu, Lei Deng et al. IEEE Transactions on Neural Networks and Learning Systems profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Man Yao China 7 274 175 127 41 37 15 366
Youngeun Kim United States 8 169 0.6× 94 0.5× 211 1.7× 119 2.9× 29 0.8× 17 360
Dingheng Wang China 9 136 0.5× 91 0.5× 116 0.9× 88 2.1× 17 0.5× 15 304
Jeff Kusnitz United States 2 476 1.7× 254 1.5× 199 1.6× 85 2.1× 85 2.3× 3 572
Byunggook Na South Korea 6 252 0.9× 159 0.9× 141 1.1× 75 1.8× 46 1.2× 10 370
Davis Barch United States 5 445 1.6× 202 1.2× 221 1.7× 79 1.9× 114 3.1× 7 540
Jiangrong Shen China 11 283 1.0× 240 1.4× 136 1.1× 37 0.9× 47 1.3× 30 384
Yanqi Chen China 5 451 1.6× 302 1.7× 207 1.6× 29 0.7× 60 1.6× 6 553
Amar Shrestha United States 10 233 0.9× 120 0.7× 97 0.8× 13 0.3× 67 1.8× 16 271
Daniel Ben Dayan Rubin United States 8 359 1.3× 232 1.3× 142 1.1× 21 0.5× 141 3.8× 9 434
Gourav Datta United States 9 168 0.6× 71 0.4× 67 0.5× 37 0.9× 28 0.8× 25 233

Countries citing papers authored by Man Yao

Since Specialization
Citations

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

Fields of papers citing papers by Man Yao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Man Yao

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

All Works

15 of 15 papers shown
1.
Zhang, Jiahong, Man Yao, Han Xu, et al.. (2025). Enhancing robustness of spiking neural networks through retina-like coding and memory-based neurons. Neural Networks. 193. 107950–107950.
2.
Yao, Man, Tianxiang Hu, Kuan Tian, et al.. (2025). Scaling Spike-Driven Transformer With Efficient Spike Firing Approximation Training. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(4). 2973–2990. 6 indexed citations
3.
Shen, Hui, et al.. (2025). A multisynaptic spiking neuron for simultaneously encoding spatiotemporal dynamics. Nature Communications. 16(1). 7155–7155. 2 indexed citations
4.
Yuan, Chunfeng, Haowei Liu, Man Yao, et al.. (2025). MSFI: Multi-timescale spatio-temporal features integration in spiking neural networks. Neural Networks. 193. 108024–108024.
5.
Zhou, Peng, Yang Tian, Ruijie Zhu, et al.. (2025). Neuromorphic spike-based large language model. National Science Review. 13(4). nwaf551–nwaf551.
6.
Yao, Man, Jieyuan Zhang, Ning Qiao, et al.. (2025). Efficient 3D Recognition with Event-driven Spike Sparse Convolution. Proceedings of the AAAI Conference on Artificial Intelligence. 39(19). 20086–20094.
7.
8.
Yao, Man, et al.. (2024). SNN-BERT: Training-efficient Spiking Neural Networks for energy-efficient BERT. Neural Networks. 180. 106630–106630. 4 indexed citations
9.
Hu, Yifan, Lei Deng, Yujie Wu, Man Yao, & Guoqi Li. (2024). Advancing Spiking Neural Networks Toward Deep Residual Learning. IEEE Transactions on Neural Networks and Learning Systems. 36(2). 2353–2367. 55 indexed citations breakdown →
10.
Yao, Man, Guangshe Zhao, Ning Qiao, et al.. (2024). Spike-based dynamic computing with asynchronous sensing-computing neuromorphic chip. Nature Communications. 15(1). 4464–4464. 45 indexed citations
11.
12.
Yao, Man, Guangshe Zhao, Xiyu Zhang, et al.. (2023). Sparser spiking activity can be better: Feature Refine-and-Mask spiking neural network for event-based visual recognition. Neural Networks. 166. 410–423. 16 indexed citations
13.
Yao, Man, Guangshe Zhao, Yifan Hu, et al.. (2023). Attention Spiking Neural Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(8). 9393–9410. 122 indexed citations breakdown →
14.
Wang, Dingheng, Guangshe Zhao, Man Yao, et al.. (2021). Kronecker CP Decomposition With Fast Multiplication for Compressing RNNs. IEEE Transactions on Neural Networks and Learning Systems. 34(5). 2205–2219. 16 indexed citations
15.
Yao, Man, Guangshe Zhao, Dingheng Wang, et al.. (2021). Temporal-wise Attention Spiking Neural Networks for Event Streams Classification. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 10201–10210. 98 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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