Peng Li

6.6k total citations · 1 hit paper
177 papers, 4.7k citations indexed

About

Peng Li is a scholar working on Electrical and Electronic Engineering, Hardware and Architecture and Artificial Intelligence. According to data from OpenAlex, Peng Li has authored 177 papers receiving a total of 4.7k indexed citations (citations by other indexed papers that have themselves been cited), including 131 papers in Electrical and Electronic Engineering, 47 papers in Hardware and Architecture and 31 papers in Artificial Intelligence. Recurrent topics in Peng Li's work include Low-power high-performance VLSI design (65 papers), Advanced Memory and Neural Computing (45 papers) and VLSI and Analog Circuit Testing (34 papers). Peng Li is often cited by papers focused on Low-power high-performance VLSI design (65 papers), Advanced Memory and Neural Computing (45 papers) and VLSI and Analog Circuit Testing (34 papers). Peng Li collaborates with scholars based in United States, China and Qatar. Peng Li's co-authors include Guoyao Wu, Garng M. Huang, Jesse Trushenski, Kangsen Mai, Yong Zhang, Zhuo Feng, Yongtae Kim, Tingwen Huang, Yulong Yin and Yingyezhe Jin and has published in prestigious journals such as Advanced Materials, Nature Communications and PLoS ONE.

In The Last Decade

Peng Li

168 papers receiving 4.6k citations

Hit Papers

align trajectories

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.

New developments in fish amino acid nutrition: towards functional and environmentally oriented aquafeeds

2008 707 citations Peng Li et al. profile →

Peers

Peng Li

EEE

AS

AI

IMMUN

HA

Hiroyuki Fujita Japan

Younghyun Kim South Korea

Tomoaki Yoshida Japan

Xin Geng China

Takayuki Hoshino Japan

Hiroshi Fujimoto Japan

Nobuyuki Yamasaki Japan

Abdul Quaiyum Ansari India

Yoshihiro Watanabe Japan

Wenbo Liu China

Hiroyuki Fujita Japan

Peng Li

5.1k ×2.2

EEE

182 ×0.3

AS

52 ×0.1

AI

17 ×0.0

IMMUN

16 ×0.0

HA

Citations per year, relative to Peng Li Peng Li (= 1×) peers Hiroyuki Fujita

Countries citing papers authored by Peng Li

Since Specialization

Citations

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

Fields of papers citing papers by Peng Li

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peng Li

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Zhang, Wenrui, et al.. (2024). Composing recurrent spiking neural networks using locally-recurrent motifs and risk-mitigating architectural optimization. Frontiers in Neuroscience. 18. 1412559–1412559.

2.

Li, Peng, et al.. (2023). Two novel models with nuclear norm for robust matrix recovery. Signal Processing. 218. 109372–109372.

3.

Zhang, Wenrui, et al.. (2022). SaARSP: An Architecture for Systolic-Array Acceleration of Recurrent Spiking Neural Networks. ACM Journal on Emerging Technologies in Computing Systems. 18(4). 1–23. 3 indexed citations

4.

Deng, Lei, Yujie Wu, Yifan Hu, et al.. (2021). Comprehensive SNN Compression Using ADMM Optimization and Activity Regularization. IEEE Transactions on Neural Networks and Learning Systems. 34(6). 2791–2805. 58 indexed citations

5.

Liang, Ling, Zheng Qu, Zhaodong Chen, et al.. (2021). H2Learn: High-Efficiency Learning Accelerator for High-Accuracy Spiking Neural Networks. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 41(11). 4782–4796. 29 indexed citations

6.

Liang, Ling, Xing Hu, Lei Deng, et al.. (2021). Exploring Adversarial Attack in Spiking Neural Networks With Spike-Compatible Gradient. IEEE Transactions on Neural Networks and Learning Systems. 34(5). 2569–2583. 37 indexed citations

7.

Zhang, Wenrui & Peng Li. (2020). Temporal Spike Sequence Learning via Backpropagation for Deep Spiking Neural Networks. eScholarship (California Digital Library). 33. 12022–12033. 10 indexed citations

8.

Sun, Bo, Shiping Wen, Shengbo Wang, et al.. (2019). Quantized synchronization of memristive neural networks with time-varying delays via super-twisting algorithm. Neurocomputing. 380. 133–140. 37 indexed citations

9.

Zhao, You, Xing He, Tingwen Huang, Junjian Huang, & Peng Li. (2019). A smoothing neural network for minimization l1-lp in sparse signal reconstruction with measurement noises. Neural Networks. 122. 40–53. 19 indexed citations

10.

Sheng, Yin, Tingwen Huang, Zhigang Zeng, & Peng Li. (2019). Exponential Stabilization of Inertial Memristive Neural Networks With Multiple Time Delays. IEEE Transactions on Cybernetics. 51(2). 579–588. 78 indexed citations

11.

Li, Peng, et al.. (2015). Abnormal event detection scheme based on compressive sensing and GM(1,1) in Wireless Sensor Networks. PolyU Institutional Research Archive (Hong Kong Polytechnic University). 1 indexed citations

12.

Li, Peng. (2012). Parallel Circuit Simulation: A Historical Perspective and Recent Developments. 5(4). 211–318. 7 indexed citations

13.

Xu, Tong, et al.. (2011). Fast static analysis of power grids: algorithms and implementations. International Conference on Computer Aided Design. 488–493. 13 indexed citations

14.

Singh, Amandeep & Peng Li. (2010). On behavioral model equivalence checking for large analog/mixed signal systems. International Conference on Computer Aided Design. 55–61. 15 indexed citations

15.

Dong, Wei, Zhuo Feng, & Peng Li. (2007). Efficient VCO phase macromodel generation considering statistical parametric variations. International Conference on Computer Aided Design. 874–878. 5 indexed citations

16.

Feng, Zhuo & Peng Li. (2007). A methodology for timing model characterization for statistical static timing analysis. International Conference on Computer Aided Design. 725–729. 3 indexed citations

17.

Li, Peng, et al.. (2007). Analysis of large clock meshes via harmonic-weighted model order reduction and port sliding. International Conference on Computer Aided Design. 627–631. 17 indexed citations

18.

Yu, Guo & Peng Li. (2007). Yield-aware analog integrated circuit optimization using geostatistics motivated performance modeling. International Conference on Computer Aided Design. 464–469. 39 indexed citations

19.

Li, Peng. (2005). Variational analysis of large power grids by exploring statistical sampling sharing and spatial locality. International Conference on Computer Aided Design. 645–651. 13 indexed citations

20.

Xu, Yang, Xin Li, Peng Li, & Lawrence T. Pileggi. (2003). Noise Macromodel for Radio Frequency Integrated Circuits. Design, Automation, and Test in Europe. 10150–10155. 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.

Explore authors with similar magnitude of impact