Liqiang Lu

1.5k total citations
38 papers, 1.1k citations indexed

About

Liqiang Lu is a scholar working on Hardware and Architecture, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Liqiang Lu has authored 38 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Hardware and Architecture, 15 papers in Computer Vision and Pattern Recognition and 14 papers in Artificial Intelligence. Recurrent topics in Liqiang Lu's work include Parallel Computing and Optimization Techniques (17 papers), Advanced Neural Network Applications (15 papers) and Quantum Computing Algorithms and Architecture (10 papers). Liqiang Lu is often cited by papers focused on Parallel Computing and Optimization Techniques (17 papers), Advanced Neural Network Applications (15 papers) and Quantum Computing Algorithms and Architecture (10 papers). Liqiang Lu collaborates with scholars based in China, United States and Hong Kong. Liqiang Lu's co-authors include Yun Liang, Shengen Yan, Qingcheng Xiao, Zizhang Luo, Yu‐Wing Tai, Wei Lin, Ruirui Huang, Peng Li, Hangrui Bi and Tao Wang and has published in prestigious journals such as IEEE Transactions on Computers, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems and IEEE Micro.

In The Last Decade

Liqiang Lu

28 papers receiving 1.0k citations

Peers

Liqiang Lu
Fengbin Tu China
Shengen Yan China
Antonio Puglielli United States
Liqiang He China
Hyoukjun Kwon United States
Jinmook Lee South Korea
Anurag Mukkara United States
Naveen Suda United States
Hardik Sharma United States
Fengbin Tu China
Liqiang Lu
Citations per year, relative to Liqiang Lu Liqiang Lu (= 1×) peers Fengbin Tu

Countries citing papers authored by Liqiang Lu

Since Specialization
Citations

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

Fields of papers citing papers by Liqiang Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Liqiang Lu

This figure shows the co-authorship network connecting the top 25 collaborators of Liqiang Lu. A scholar is included among the top collaborators of Liqiang Lu 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 Liqiang Lu. Liqiang Lu 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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Fu, Teng, Miao Pan, Xuhong Zhang, et al.. (2025). VeriRL: Boosting the LLM-based Verilog Code Generation via Reinforcement Learning. 1–9.
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Luo, Zizhang, Liqiang Lu, Size Zheng, et al.. (2023). Rubick: A Synthesis Framework for Spatial Architectures via Dataflow Decomposition. 1–6. 6 indexed citations
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Luo, Zizhang, et al.. (2022). Automatic Generation of Spatial Accelerator for Tensor Algebra. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 42(6). 1898–1911. 3 indexed citations
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Zheng, Size, et al.. (2022). AMOS. 874–887. 37 indexed citations
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Liang, Yun, et al.. (2021). FCNNLib: A Flexible Convolution Algorithm Library for Deep Learning on FPGAs. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 41(8). 2546–2559. 11 indexed citations
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Lu, Liqiang, Yuyue Wang, Zizhang Luo, et al.. (2021). TENET: A Framework for Modeling Tensor Dataflow Based on Relation-centric Notation. 720–733. 52 indexed citations
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Lu, Liqiang, Hangrui Bi, Zizhang Luo, et al.. (2021). Sanger: A Co-Design Framework for Enabling Sparse Attention using Reconfigurable Architecture. 977–991. 116 indexed citations
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Lu, Liqiang & Yun Liang. (2021). Morphling: A Reconfigurable Architecture for Tensor Computation. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 41(11). 4733–4746. 1 indexed citations
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Luo, Zizhang, et al.. (2021). Analyzing the Design Space of Spatial Tensor Accelerators on FPGAs. 230–235. 1 indexed citations
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Liang, Yun, et al.. (2020). OMNI: A Framework for Integrating Hardware and Software Optimizations for Sparse CNNs. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 40(8). 1648–1661. 31 indexed citations
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Liang, Yun, et al.. (2020). Enabling Efficient Fast Convolution Algorithms on GPUs via MegaKernels. IEEE Transactions on Computers. 1–1. 10 indexed citations
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Lu, Liqiang, et al.. (2019). An Efficient Hardware Accelerator for Sparse Convolutional Neural Networks on FPGAs. 17–25. 111 indexed citations
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Lu, Liqiang, et al.. (2019). Speedy. 187–187. 4 indexed citations
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Lu, Liqiang & Yun Liang. (2018). SpWA. 1–6. 52 indexed citations
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Lu, Liqiang, Yun Liang, Qingcheng Xiao, & Shengen Yan. (2017). Evaluating Fast Algorithms for Convolutional Neural Networks on FPGAs. 101–108. 193 indexed citations
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Cheng, Gang, Ying Zhang, & Liqiang Lu. (2011). Efficient algorithms for computing the non and semi-parametric maximum likelihood estimates with panel count data. Journal of nonparametric statistics. 23(2). 567–579. 8 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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