Li Du

992 total citations
87 papers, 554 citations indexed

About

Li Du is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Li Du has authored 87 papers receiving a total of 554 indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Electrical and Electronic Engineering, 21 papers in Computer Vision and Pattern Recognition and 21 papers in Artificial Intelligence. Recurrent topics in Li Du's work include Advanced Memory and Neural Computing (20 papers), Advanced Neural Network Applications (17 papers) and CCD and CMOS Imaging Sensors (12 papers). Li Du is often cited by papers focused on Advanced Memory and Neural Computing (20 papers), Advanced Neural Network Applications (17 papers) and CCD and CMOS Imaging Sensors (12 papers). Li Du collaborates with scholars based in China, United States and Taiwan. Li Du's co-authors include Yuan Du, Mau-Chung Frank Chang, Yilei Li, Yen‐Cheng Kuan, Junjie Su, Zhongfeng Wang, Jiang Zhe, Jun Lin, Abhay Vasudev and Ashish V. Jagtiani and has published in prestigious journals such as Sensors, IEEE Journal of Solid-State Circuits and Journal of Lightwave Technology.

In The Last Decade

Li Du

68 papers receiving 542 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Li Du China 11 349 181 124 59 50 87 554
Sungpill Choi South Korea 14 438 1.3× 324 1.8× 154 1.2× 50 0.8× 64 1.3× 36 682
Jong Hwan Ko South Korea 16 290 0.8× 300 1.7× 156 1.3× 53 0.9× 76 1.5× 88 702
Taesik Na United States 12 283 0.8× 147 0.8× 109 0.9× 53 0.9× 35 0.7× 29 403
Shimpei Sato Japan 12 371 1.1× 310 1.7× 147 1.2× 22 0.4× 74 1.5× 52 588
Mingyu Wang China 12 190 0.5× 144 0.8× 80 0.6× 38 0.6× 36 0.7× 75 427
Junbin Wang China 6 277 0.8× 329 1.8× 153 1.2× 17 0.3× 30 0.6× 8 487
Kamal El‐Sankary Canada 13 392 1.1× 113 0.6× 102 0.8× 234 4.0× 70 1.4× 103 590
Babita R. Jose India 10 186 0.5× 125 0.7× 95 0.8× 55 0.9× 58 1.2× 66 367
Jinshan Yue China 15 689 2.0× 325 1.8× 187 1.5× 33 0.6× 81 1.6× 73 905

Countries citing papers authored by Li Du

Since Specialization
Citations

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

Fields of papers citing papers by Li Du

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Li Du

This figure shows the co-authorship network connecting the top 25 collaborators of Li Du. A scholar is included among the top collaborators of Li Du 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 Li Du. Li Du 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.
Du, Yuan, et al.. (2024). An 11T1C Bit-Level-Sparsity-Aware Computing- in-Memory Macro With Adaptive Conversion Time and Computation Voltage. IEEE Transactions on Circuits and Systems I Regular Papers. 71(11). 4985–4995. 1 indexed citations
2.
Du, Yuan, et al.. (2024). A Compilation Framework for SRAM Computing-in-Memory Systems With Optimized Weight Mapping and Error Correction. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 43(8). 2379–2392. 2 indexed citations
3.
Zhang, Rongyu, Huanrui Yang, Denis Gudovskiy, et al.. (2024). VeCAF: Vision-language Collaborative Active Finetuning with Training Objective Awareness. 5451–5459. 3 indexed citations
4.
5.
Zhang, Xiaopeng, et al.. (2024). An Area-Efficient CNN Accelerator Supporting Global Average Pooling with Arbitrary Shapes. 413–416. 2 indexed citations
6.
Du, Li, et al.. (2024). Low-Latency DAE: A Configurable Lightweight Hybrid Data and Address Encryption Engine for IoT Real-Time NVM Protection. IEEE Internet of Things Journal. 12(7). 8438–8452.
7.
Zhang, Rongyu, Jiaming Liu, Xiaowei Chi, et al.. (2024). BEVUDA++: Geometric-Aware Unsupervised Domain Adaptation for Multi-View 3D Object Detection. IEEE Transactions on Circuits and Systems for Video Technology. 35(5). 5109–5122. 1 indexed citations
8.
9.
Liu, Jiaming, et al.. (2023). BEV-LGKD: A Unified LiDAR-Guided Knowledge Distillation Framework for Multi-View BEV 3D Object Detection. IEEE Transactions on Intelligent Vehicles. 9(1). 2489–2498. 11 indexed citations
10.
Liu, Yujia, et al.. (2023). Low-Latency PAE: Permutation-Based Address Encryption Hardware Engine for IoT Real-Time Memory Protection. IEEE Internet of Things Journal. 11(7). 12319–12330. 1 indexed citations
11.
Zhao, Ning, et al.. (2023). An Efficient CNN Inference Accelerator Based on Intra- and Inter-Channel Feature Map Compression. IEEE Transactions on Circuits and Systems I Regular Papers. 70(9). 3625–3638. 2 indexed citations
12.
Lu, Xin, et al.. (2023). SSM-CIM: An Efficient CIM Macro Featuring Single-Step Multi-bit MAC Computation for CNN Edge Inference. IEEE Transactions on Circuits and Systems I Regular Papers. 70(11). 4357–4368. 10 indexed citations
13.
Du, Li, et al.. (2023). A 31–46 GHz Dual-Core Class-C VCO Using Switchable Transformers in 28-nm CMOS. IEEE Microwave and Wireless Technology Letters. 33(9). 1341–1344. 2 indexed citations
14.
Wang, Leilei, Qi Sun, Zijiang Yang, et al.. (2023). Optical Circuit Switching Using REC-DFB Laser Array. Journal of Lightwave Technology. 42(8). 2880–2886. 4 indexed citations
15.
Zhang, Yuhang, Yanhan Zeng, Zhihong Luo, et al.. (2023). Design of All-Digital Two Phase Ping-Pong Switched Capacitor Voltage Doubler Power Converter. IEEE Transactions on Circuits & Systems II Express Briefs. 70(10). 3807–3811. 1 indexed citations
16.
Du, Yuan, et al.. (2023). An Energy-Efficient Spiking Neural Network Accelerator Based on Spatio-Temporal Redundancy Reduction. IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 32(4). 782–786. 2 indexed citations
17.
Du, Yuan, et al.. (2021). Characterization of Programmable Charge-Trap Transistors (CTTs) in Standard 28-nm CMOS for Nonvolatile Memory and Analog Arithmetic Applications. IEEE Journal on Exploratory Solid-State Computational Devices and Circuits. 7(1). 10–17. 4 indexed citations
18.
Du, Li, et al.. (2021). Memory-Efficient CNN Accelerator Based on Interlayer Feature Map Compression. IEEE Transactions on Circuits and Systems I Regular Papers. 69(2). 668–681. 24 indexed citations
19.
Du, Yuan, et al.. (2018). An Analog Neural Network Computing Engine Using CMOS-Compatible Charge-Trap-Transistor (CTT). IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 38(10). 1811–1819. 28 indexed citations
20.
Li, Yilei, Yuan Du, Li Du, et al.. (2017). A Novel Fully Synthesizable All-Digital RF Transmitter for IoT Applications. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 37(1). 146–158. 6 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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