Yang Yi

3.3k total citations
147 papers, 2.3k citations indexed

About

Yang Yi is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Yang Yi has authored 147 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 131 papers in Electrical and Electronic Engineering, 71 papers in Artificial Intelligence and 36 papers in Cognitive Neuroscience. Recurrent topics in Yang Yi's work include Advanced Memory and Neural Computing (86 papers), Neural Networks and Reservoir Computing (62 papers) and Neural dynamics and brain function (34 papers). Yang Yi is often cited by papers focused on Advanced Memory and Neural Computing (86 papers), Neural Networks and Reservoir Computing (62 papers) and Neural dynamics and brain function (34 papers). Yang Yi collaborates with scholars based in United States, China and Chile. Yang Yi's co-authors include Lingjia Liu, Jinsong Wu, Hao Song, Rachad Atat, Jianzhong Zhang, Hao-Hsuan Chang, Jianan Bai, Bodong Shang, Hongyu An and Chenyuan Zhao and has published in prestigious journals such as IEEE Access, IEEE Transactions on Communications and IEEE Transactions on Wireless Communications.

In The Last Decade

Yang Yi

142 papers receiving 2.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yang Yi United States 26 1.7k 857 794 337 229 147 2.3k
Ulrich Rückert Germany 22 1.0k 0.6× 638 0.7× 610 0.8× 106 0.3× 150 0.7× 255 2.2k
Hun-Seok Kim United States 25 1.5k 0.9× 513 0.6× 1.3k 1.7× 139 0.4× 149 0.7× 142 3.0k
Mahmoud Al‐Qutayri United Arab Emirates 27 1.4k 0.9× 442 0.5× 668 0.8× 84 0.2× 157 0.7× 215 2.5k
Davide Rossi Italy 27 1.6k 0.9× 547 0.6× 875 1.1× 203 0.6× 79 0.3× 204 2.9k
Masoud Daneshtalab Finland 30 1.4k 0.9× 262 0.3× 2.1k 2.6× 183 0.5× 82 0.4× 220 3.1k
Cong Xu China 19 2.2k 1.3× 724 0.8× 558 0.7× 263 0.8× 52 0.2× 47 3.0k
Hassan Mostafa Egypt 20 1.3k 0.8× 230 0.3× 301 0.4× 165 0.5× 113 0.5× 271 1.9k
Weng‐Fai Wong Singapore 29 984 0.6× 476 0.6× 1.3k 1.6× 149 0.4× 30 0.1× 182 2.8k
Jyoteesh Malhotra India 25 1.6k 0.9× 137 0.2× 796 1.0× 236 0.7× 247 1.1× 192 2.4k
Alex Yakovlev United Kingdom 27 2.5k 1.5× 501 0.6× 1.2k 1.5× 56 0.2× 40 0.2× 498 4.3k

Countries citing papers authored by Yang Yi

Since Specialization
Citations

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

Fields of papers citing papers by Yang Yi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yang Yi

This figure shows the co-authorship network connecting the top 25 collaborators of Yang Yi. A scholar is included among the top collaborators of Yang Yi 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 Yang Yi. Yang Yi 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.
Sharma, G. K., et al.. (2025). SpikeSpec: An On-Chip Learning Neuromorphic Accelerator for Spectrum Sensing With Triplet-Boosting and Hardware Friendly Loss Function. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 44(9). 3423–3436. 1 indexed citations
2.
Chang, Hao-Hsuan, et al.. (2024). Dyna-ESN: Efficient Deep Reinforcement Learning for Partially Observable Dynamic Spectrum Access. IEEE Transactions on Wireless Communications. 24(6). 4517–4531. 1 indexed citations
3.
4.
Yi, Yang, et al.. (2024). Leveraging neuro-inspired AI accelerator for high-speed computing in 6G networks. Frontiers in Computational Neuroscience. 18. 1345644–1345644.
5.
An, Hongyu, et al.. (2023). Towards Energy-Efficient Spiking Neural Networks: A Robust Hybrid CMOS-Memristive Accelerator. ACM Journal on Emerging Technologies in Computing Systems. 20(1). 1–20. 5 indexed citations
6.
Huang, Yi, et al.. (2023). MERRC: A Memristor-Enabled Reconfigurable Low-Power Reservoir Computing Architecture at the Edge. IEEE Transactions on Circuits and Systems I Regular Papers. 71(1). 174–186. 7 indexed citations
7.
Yi, Yang, et al.. (2023). Spiking Neural Encoding Schemes and STDP Training Algorithms for Edge Computing. VTechWorks (Virginia Tech). 365–371.
8.
Chang, Hao-Hsuan, et al.. (2021). Resource Allocation for D2D Cellular Networks With QoS Constraints: A DC Programming- Based Approach. IEEE Access. 10. 16424–16438. 7 indexed citations
9.
Zhou, Zhou, et al.. (2021). RCNet: Incorporating Structural Information Into Deep RNN for Online MIMO-OFDM Symbol Detection With Limited Training. IEEE Transactions on Wireless Communications. 20(6). 3524–3537. 28 indexed citations
10.
Ha, Dong Sam, et al.. (2021). Efficient neural networks for edge devices. Computers & Electrical Engineering. 92. 107121–107121. 13 indexed citations
11.
Yi, Yang, et al.. (2020). Moving Toward Intelligence: Detecting Symbols on 5G Systems Through Deep Echo State Network. IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 10(2). 253–263. 16 indexed citations
12.
Chang, Hao-Hsuan, Lingjia Liu, & Yang Yi. (2020). Deep Echo State Q-Network (DEQN) and Its Application in Dynamic Spectrum Sharing for 5G and Beyond. IEEE Transactions on Neural Networks and Learning Systems. 33(3). 929–939. 43 indexed citations
13.
Shang, Bodong, et al.. (2020). A Cross-Layer Optimization Framework for Distributed Computing in IoT Networks. 440–444. 5 indexed citations
14.
Wang, Chenguang, et al.. (2018). Control System Design for Micro AUV Based on Open Source Hardware. 980–984. 2 indexed citations
15.
Ehsan, M. Amimul, Zhen Zhou, & Yang Yi. (2017). Hybrid three-dimensional integrated circuits: A viable solution for high efficiency Neuromorphic Computing. 1–2. 1 indexed citations
16.
Ehsan, M. Amimul, Zhen Zhou, & Yang Yi. (2016). Modeling and optimization of TSV for crosstalk mitigation in 3D neuromorphic system. 621–626. 3 indexed citations
17.
Ehsan, M. Amimul, Hongyu An, Zhen Zhou, & Yang Yi. (2016). Design challenges and methodologies in 3D integration for neuromorphic computing systems. 24–28. 6 indexed citations
18.
Ehsan, M. Amimul, Zhen Zhou, & Yang Yi. (2014). Electrical modeling and analysis of sidewall roughness of through silicon vias in 3D integration. 52–56. 12 indexed citations
19.
Yi, Yang. (2013). On Improvement in Design of Scanning Circuit for 4*4 Keyboard Based on the FPGA. Journal of Southwest China Normal University. 1 indexed citations
20.
Yi, Yang. (2001). Modeling and Application of a Double Inverted Pendulum. Journal of Hebei University of Technology. 1 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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