Zheyu Yan

471 total citations
25 papers, 259 citations indexed

About

Zheyu Yan is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Zheyu Yan has authored 25 papers receiving a total of 259 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Electrical and Electronic Engineering, 10 papers in Artificial Intelligence and 9 papers in Computer Vision and Pattern Recognition. Recurrent topics in Zheyu Yan's work include Advanced Memory and Neural Computing (12 papers), Ferroelectric and Negative Capacitance Devices (9 papers) and Advanced Neural Network Applications (8 papers). Zheyu Yan is often cited by papers focused on Advanced Memory and Neural Computing (12 papers), Ferroelectric and Negative Capacitance Devices (9 papers) and Advanced Neural Network Applications (8 papers). Zheyu Yan collaborates with scholars based in United States, China and Japan. Zheyu Yan's co-authors include Yiyu Shi, Xiaobo Sharon Hu, Weiwen Jiang, Lei Yang, Jingtong Hu, Vikas Chandra, Liangzhen Lai, Hyoukjun Kwon, Tushar Krishna and B.L. Wang and has published in prestigious journals such as Composites Part B Engineering, IEEE Transactions on Computers and IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

In The Last Decade

Zheyu Yan

19 papers receiving 256 citations

Peers

Zheyu Yan
Yukun Ding United States
Mengyun Liu United States
Gokul Krishnan United States
Wantong Li United States
Shuhao Jiang China
Nandhini Chandramoorthy United States
Xingyu Liu China
Na Gong United States
Sarthak Gupta India
Yukun Ding United States
Zheyu Yan
Citations per year, relative to Zheyu Yan Zheyu Yan (= 1×) peers Yukun Ding

Countries citing papers authored by Zheyu Yan

Since Specialization
Citations

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

Fields of papers citing papers by Zheyu Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zheyu Yan

This figure shows the co-authorship network connecting the top 25 collaborators of Zheyu Yan. A scholar is included among the top collaborators of Zheyu Yan 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 Zheyu Yan. Zheyu Yan 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
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Yan, Zheyu, Junshi Xia, Zixuan Pan, et al.. (2025). NeFT: Negative Feedback Training to Improve Robustness of Compute-in-Memory DNN Accelerators. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 45(2). 983–997.
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Yan, Zheyu, Zhaoxuan Tan, Meng Jiang, et al.. (2025). Empirical Guidelines for Deploying LLMs onto Resource-constrained Edge Devices. ACM Transactions on Design Automation of Electronic Systems. 30(5). 1–58. 5 indexed citations
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Yan, Zheyu, Liu Liu, Jinjun Xiong, et al.. (2025). NVCiM-PT: An NVCiM-Assisted Prompt Tuning Framework for Edge LLMs. 1–7.
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Yan, Zheyu, Dawen Zeng, Ahmed Abbasi, et al.. (2024). Robust Implementation of Retrieval-Augmented Generation on Edge-based Computing-in-Memory Architectures. 1–9. 4 indexed citations
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Yan, Zheyu, et al.. (2024). Hardware design and the fairness of a neural network. Nature Electronics. 7(8). 714–723. 1 indexed citations
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Yan, Zheyu, Xiaobo Sharon Hu, & Yiyu Shi. (2024). U-SWIM: Universal Selective Write-Verify for Computing-in-Memory Neural Accelerators. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 43(6). 1822–1833. 2 indexed citations
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Yan, Zheyu, et al.. (2024). Personalized Meta-Federated Learning for IoT-Enabled Health Monitoring. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 43(10). 3157–3170. 1 indexed citations
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Yan, Zheyu, Xiaobo Sharon Hu, & Yiyu Shi. (2024). Compute-in-Memory-Based Neural Network Accelerators for Safety-Critical Systems: Worst-Case Scenarios and Protections. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 43(8). 2452–2464. 1 indexed citations
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Wang, Tianchen, Jiawei Zhang, Jinjun Xiong, et al.. (2022). VisualNet: An End-to-End Human Visual System Inspired Framework to Reduce Inference Latency of Deep Neural Networks. IEEE Transactions on Computers. 71(11). 2717–2727. 6 indexed citations
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Yan, Zheyu, Weiwen Jiang, Xiaobo Sharon Hu, & Yiyu Shi. (2022). RADARS: Memory Efficient Reinforcement Learning Aided Differentiable Neural Architecture Search. 128–133. 5 indexed citations
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Yan, Zheyu, Xiaobo Sharon Hu, & Yiyu Shi. (2022). SWIM. Proceedings of the 59th ACM/IEEE Design Automation Conference. 277–282. 16 indexed citations
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Jiang, Weiwen, Zheyu Yan, Lei Yang, et al.. (2020). Device-Circuit-Architecture Co-Exploration for Computing-in-Memory Neural Accelerators. IEEE Transactions on Computers. 70(4). 595–605. 60 indexed citations
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Yang, Lei, Zheyu Yan, Hyoukjun Kwon, et al.. (2020). Co-Exploration of Neural Architectures and Heterogeneous ASIC Accelerator Designs Targeting Multiple Tasks. 1–6. 63 indexed citations
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Yan, Zheyu, Yiyu Shi, Wang Liao, et al.. (2020). When Single Event Upset Meets Deep Neural Networks: Observations, Explorations, and Remedies. 163–168. 34 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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