Ligeng Zhu

4.0k total citations
13 papers, 420 citations indexed

About

Ligeng Zhu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Ligeng Zhu has authored 13 papers receiving a total of 420 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 7 papers in Artificial Intelligence and 2 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Ligeng Zhu's work include Advanced Neural Network Applications (6 papers), Machine Learning and ELM (2 papers) and Privacy-Preserving Technologies in Data (2 papers). Ligeng Zhu is often cited by papers focused on Advanced Neural Network Applications (6 papers), Machine Learning and ELM (2 papers) and Privacy-Preserving Technologies in Data (2 papers). Ligeng Zhu collaborates with scholars based in United States. Ligeng Zhu's co-authors include Song Han, Han Cai, Zhijian Liu, Hanrui Wang, Chuang Gan, Ji Lin, Zhanghao Wu, Yujun Lin, Wei-Ming Chen and Haotian Tang and has published in prestigious journals such as IEEE Transactions on Image Processing, IEEE Micro and IEEE Circuits and Systems Magazine.

In The Last Decade

Ligeng Zhu

11 papers receiving 409 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ligeng Zhu United States	9	232	203	79	51	26	13	420
Manuele Rusci Italy	10	142 0.6×	122 0.6×	137 1.7×	68 1.3×	31 1.2×	29	362
Maurizio Capra Italy	5	116 0.5×	108 0.5×	172 2.2×	87 1.7×	45 1.7×	7	365
Seong‐heum Kim South Korea	8	137 0.6×	90 0.4×	37 0.5×	41 0.8×	9 0.3×	18	323
Babita R. Jose India	10	125 0.5×	95 0.5×	186 2.4×	58 1.1×	14 0.5×	66	367
Alexandros Kouris United Kingdom	8	159 0.7×	89 0.4×	87 1.1×	35 0.7×	53 2.0×	13	328
Joel Janai Germany	5	261 1.1×	128 0.6×	42 0.5×	23 0.5×	7 0.3×	5	449

Countries citing papers authored by Ligeng Zhu

Since Specialization

Citations

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

Fields of papers citing papers by Ligeng Zhu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ligeng Zhu

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

All Works

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13 of 13 papers shown

Lin, Ji, et al.. (2023). Tiny Machine Learning: Progress and Futures [Feature]. IEEE Circuits and Systems Magazine. 23(3). 8–34. 62 indexed citations

Wang, Wei-Chen, et al.. (2022). On-Device Training Under 256KB Memory. 22941–22954.

Cai, Han, Ji Lin, Yujun Lin, et al.. (2022). Enable Deep Learning on Mobile Devices: Methods, Systems, and Applications. ACM Transactions on Design Automation of Electronic Systems. 27(3). 1–50. 85 indexed citations

Zhu, Ligeng, et al.. (2021). Delayed Gradient Averaging: Tolerate the Communication Latency for Federated Learning. Neural Information Processing Systems. 34. 16 indexed citations

Cai, Han, Chuang Gan, Ligeng Zhu, & Song Han. (2020). TinyTL: Reduce Memory, Not Parameters for Efficient On-Device Learning. arXiv (Cornell University). 33. 11285–11297. 27 indexed citations

Cai, Han, Chuang Gan, Ligeng Zhu, & Song Han. (2020). Tiny Transfer Learning: Towards Memory-Efficient On-Device Learning. arXiv (Cornell University). 8 indexed citations

Wang, Hanrui, Zhanghao Wu, Zhijian Liu, et al.. (2020). HAT: Hardware-Aware Transformers for Efficient Natural Language Processing. 7675–7688. 134 indexed citations

Cai, Han, Ji Lin, Yujun Lin, et al.. (2019). AutoML for Architecting Efficient and Specialized Neural Networks. IEEE Micro. 40(1). 75–82. 15 indexed citations

Zhu, Ligeng, Yao Lu, Yujun Lin, & Song Han. (2019). Distributed Training Across the World. 2 indexed citations

10.

Guo, Dazhou, Ligeng Zhu, Yuhang Lu, Hongkai Yu, & Song Wang. (2018). Small Object Sensitive Segmentation of Urban Street Scene With Spatial Adjacency Between Object Classes. IEEE Transactions on Image Processing. 28(6). 2643–2653. 43 indexed citations

11.

Funt, Brian & Ligeng Zhu. (2018). Does Colour Really Matter? Evaluation via Object Classification. Color and Imaging Conference. 26(1). 268–271. 7 indexed citations

12.

Zhu, Ligeng & Brian Funt. (2018). Colorizing Color Images. Electronic Imaging. 30(14). 1–6. 1 indexed citations

13.

Yang, Luwei, Ligeng Zhu, Yichen Wei, Shuang Liang, & Ping Tan. (2016). Attribute Recognition from Adaptive Parts. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 81.1–81.11. 20 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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Breakdown of academic impact, for papers by Manuele Rusci Breakdown of academic impact, for papers by Maurizio Capra Breakdown of academic impact, for papers by Seong‐heum Kim Breakdown of academic impact, for papers by Babita R. Jose Breakdown of academic impact, for papers by Alexandros Kouris Breakdown of academic impact, for papers by Joel Janai