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Guoqi Li

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Engineering and Technology 47 4748 4569 925 921 215 11755

Guoqi Li publications per year

The chart shows the history of publications by Guoqi Li between 2000 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Guoqi Li published across 26 years, from 2000 to 2025, averaging 13.7 papers a year. Output peaked at 49 publications in 2024. 71 of the 357 publications appeared in the last two years.

No. of publications
10 20 30 40
Bar chart. Horizontal axis: year, 2000 to 2025. Vertical axis: number of publications, 0 to 49. Peak 49 publications in 2024. 2000: 1 publication 2001: 3 publications 2002: 2 publications 2003: 1 publication 2004: 2 publications 2005: 0 publications 2006: 1 publication 2007: 0 publications 2008: 1 publication 2009: 4 publications 2010: 4 publications 2011: 8 publications 2012: 5 publications 2013: 7 publications 2014: 10 publications 2015: 19 publications 2016: 13 publications 2017: 16 publications 2018: 30 publications 2019: 26 publications 2020: 35 publications 2021: 31 publications 2022: 34 publications 2023: 33 publications 2024: 49 publications 2025: 22 publications
2000 2025

357 publications in total across all disciplines

View publications per year as a table
Guoqi Li: publications per year, 2000 to 2025
Year Publications
2000 1
2001 3
2002 2
2003 1
2004 2
2005 0
2006 1
2007 0
2008 1
2009 4
2010 4
2011 8
2012 5
2013 7
2014 10
2015 19
2016 13
2017 16
2018 30
2019 26
2020 35
2021 31
2022 34
2023 33
2024 49
2025 22
Total 357
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Guoqi Li publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Guoqi Li sits on this spectrum.

No. of scientists
100 200 300 400
Bar chart with 78 bars. Horizontal axis: publications, 38–47 to 804+. Vertical axis: number of scientists, 0 to 457. Most scientists, 457, have 148–157 publications. The last bar groups every scientist with 804 publications or more. The highlighted bar, 208–217 publications, is where this scientist sits. 38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38–47 publications 804+

This scientist: 215 publications — 53rd percentile

53% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

View publications distribution as a table
Number of Engineering and Technology scientists by publication count, Research.com 2026 ranking edition. Based on 9,796 ranked scientists.
Publications Scientists This scientist
38–47 20
48–57 35
58–67 96
68–77 135
78–87 190
88–97 259
98–107 283
108–117 369
118–127 341
128–137 386
138–147 372
148–157 457
158–167 415
168–177 407
178–187 421
188–197 378
198–207 403
208–217 317 215
218–227 346
228–237 321
238–247 260
248–257 280
258–267 240
268–277 214
278–287 242
288–297 203
298–307 166
308–317 154
318–327 175
328–337 159
338–347 99
348–357 131
358–367 106
368–377 118
378–387 97
388–397 108
398–407 82
408–417 71
418–427 64
428–437 55
438–447 54
448–457 60
458–467 47
468–477 40
478–487 30
488–497 29
498–507 38
508–517 40
518–527 32
528–537 23
538–547 28
548–557 23
558–567 19
568–577 16
578–587 17
588–597 18
598–607 22
608–617 15
618–627 9
628–637 11
638–647 21
648–657 12
658–667 9
668–677 11
678–687 9
688–697 6
698–707 14
708–717 7
718–727 8
728–737 10
738–747 9
748–757 5
758–767 5
768–777 11
778–787 7
788–797 2
798–803 4
804+ 100
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Guoqi Li D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Guoqi Li sits on this spectrum.

No. of scientists
100 200 300 400
Bar chart with 78 bars. Horizontal axis: D-Index, 30 to 107+. Vertical axis: number of scientists, 0 to 426. Most scientists, 426, have 42 D-Index. The last bar groups every scientist with 107 D-Index or more. The highlighted bar, 47 D-Index, is where this scientist sits. 30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 47 D-Index — 52nd percentile

52% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

View D-Index distribution as a table
Number of Engineering and Technology scientists by D-index, Research.com 2026 ranking edition. Based on 9,796 ranked scientists.
D-Index Scientists This scientist
30 59
31 114
32 129
33 189
34 200
35 262
36 311
37 312
38 350
39 385
40 348
41 362
42 426
43 380
44 310
45 341
46 301
47 306 47
48 271
49 246
50 210
51 253
52 213
53 221
54 195
55 186
56 170
57 167
58 166
59 144
60 152
61 141
62 138
63 131
64 118
65 114
66 119
67 95
68 87
69 77
70 89
71 69
72 54
73 46
74 55
75 54
76 49
77 53
78 46
79 28
80 39
81 36
82 24
83 26
84 36
85 18
86 25
87 19
88 26
89 27
90 23
91 15
92 12
93 9
94 15
95 10
96 13
97 13
98 9
99 7
100 7
101 8
102 7
103 7
104 9
105 6
106 9
107+ 99
Download as CSV

Overview

Guoqi Li is affiliated with Shanghai Jiao Tong University in China. Their research spans numerous topics within computer science and engineering, with a substantial focus on neural networks, brain-inspired computing, and advanced neural computing technologies.

Their published work covers a broad range of fields including:

  • Computer Science
  • Engineering

Within these fields, more specialized subfields of study include:

  • Electrical and Electronic Engineering
  • Artificial Intelligence
  • Cognitive Neuroscience
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

Key topics addressed in Guoqi Li's research include:

  • Advanced Memory and Neural Computing
  • Neural dynamics and brain function
  • Ferroelectric and Negative Capacitance Devices
  • Neural Networks and Reservoir Computing
  • Advanced Neural Network Applications
  • Neural Networks and Applications
  • Complex Network Analysis Techniques

Guoqi Li has published extensively, with several notable papers demonstrating a focus on neural network optimization, brain-inspired computing, and machine learning frameworks. Selected recent publications include:

  • "Model Compression and Hardware Acceleration for Neural Networks: A Comprehensive Survey" (2020), Proceedings of the IEEE
  • "Going Deeper With Directly-Trained Larger Spiking Neural Networks" (2021), Proceedings of the AAAI Conference on Artificial Intelligence
  • "Learning to Prompt for Open-Vocabulary Object Detection with Vision-Language Model" (2022), 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "SpikingJelly: An open-source machine learning infrastructure platform for spike-based intelligence" (2023), Science Advances
  • "A system hierarchy for brain-inspired computing" (2020), Nature

Frequent co-authors in Guoqi Li's collaborative work include:

  • Lei Deng
  • Yuan Xie
  • Man Yao
  • Yujie Wu
  • Yonghong Tian

Their research is frequently published in well-regarded venues, with a significant number of contributions appearing in:

  • arXiv (Cornell University)
  • Neural Networks
  • IEEE Transactions on Neural Networks and Learning Systems
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • SSRN Electronic Journal

Best Publications

  • Spatio-Temporal Backpropagation for Training High-Performance Spiking Neural Networks.

    Yujie Wu;Lei Deng;Lei Deng;Guoqi Li;Jun Zhu

  • Towards artificial general intelligence with hybrid Tianjic chip architecture.

    Jing Pei;Lei Deng;Sen Song;Sen Song;Mingguo Zhao

  • Model Compression and Hardware Acceleration for Neural Networks: A Comprehensive Survey

    Lei Deng;Guoqi Li;Song Han;Luping Shi

  • Direct Training for Spiking Neural Networks: Faster, Larger, Better

    Yujie Wu;Lei Deng;Guoqi Li;Jun Zhu

  • CIFAR10-DVS: An Event-Stream Dataset for Object Classification.

    Hongmin Li;Hanchao Liu;Xiangyang Ji;Guoqi Li

  • Going Deeper With Directly-Trained Larger Spiking Neural Networks.

    Hanle Zheng;Yujie Wu;Lei Deng;Yifan Hu

  • Training and Inference with Integers in Deep Neural Networks

    Shuang Wu;Guoqi Li;Feng Chen;Luping Shi

  • Rethinking the performance comparison between SNNS and ANNS.

    Lei Deng;Lei Deng;Yujie Wu;Xing Hu;Ling Liang

  • Adaptive Event-Triggered Control of Nonlinear Systems With Controller and Parameter Estimator Triggering

    Jiangshuai Huang;Wei Wang;Changyun Wen;Guoqi Li

  • A system hierarchy for brain-inspired computing

    Youhui Zhang;Peng Qu;Yu Ji;Weihao Zhang

  • Motor Imagery EEG Signals Decoding by Multivariate Empirical Wavelet Transform-Based Framework for Robust Brain–Computer Interfaces

    Muhammad Tariq Sadiq;Xiaojun Yu;Zhaohui Yuan;Fan Zeming

  • Adaptive Crystallite Kinetics in Homogenous Bilayer Oxide Memristor for Emulating Diverse Synaptic Plasticity

    Jun Yin;Fei Zeng;Fei Zeng;Qin Wan;Fan Li

  • $L1$ -Norm Batch Normalization for Efficient Training of Deep Neural Networks

    Shuang Wu;Guoqi Li;Lei Deng;Liu Liu

  • Tianjic: A Unified and Scalable Chip Bridging Spike-Based and Continuous Neural Computation

    Lei Deng;Guanrui Wang;Guoqi Li;Shuangchen Li

  • Comparing SNNs and RNNs on neuromorphic vision datasets: Similarities and differences.

    Weihua He;Weihua He;YuJie Wu;Lei Deng;Guoqi Li

  • Temporal-Wise Attention Spiking Neural Networks for Event Streams Classification

    Man Yao;Huanhuan Gao;Guangshe Zhao;Dingheng Wang

  • A Tandem Learning Rule for Effective Training and Rapid Inference of Deep Spiking Neural Networks

    Jibin Wu;Yansong Chua;Malu Zhang;Guoqi Li

  • GXNOR-Net: Training deep neural networks with ternary weights and activations without full-precision memory under a unified discretization framework.

    Lei Deng;Lei Deng;Peng Jiao;Jing Pei;Zhenzhi Wu

  • Distributed adaptive leader–follower and leaderless consensus control of a class of strict-feedback nonlinear systems : a unified approach

    Jiangshuai Huang;Wei Wang;Changyun Wen;Jing Zhou

  • Direct Training for Spiking Neural Networks: Faster, Larger, Better

    Yujie Wu;Lei Deng;Guoqi Li;Jun Zhu

  • Motor Imagery EEG Signals Classification Based on Mode Amplitude and Frequency Components Using Empirical Wavelet Transform

    Muhammad Tariq Sadiq;Xiaojun Yu;Zhaohui Yuan;Zeming Fan

  • Continuous and Noninvasive Blood Pressure Measurement: A Novel Modeling Methodology of the Relationship Between Blood Pressure and Pulse Wave Velocity

    Yan Chen;Changyun Wen;Guocai Tao;Min Bi

Frequent Co-Authors

Changyun Wen
Changyun Wen Nanyang Technological University
Luping Shi
Luping Shi Tsinghua University
Yuan Xie
Yuan Xie Hong Kong University of Science and Technology
Gaoxi Xiao
Gaoxi Xiao Nanyang Technological University
Fei Zeng
Fei Zeng Tsinghua University
Jiangshuai Huang
Jiangshuai Huang Chongqing University
Haizhou Li
Haizhou Li Chinese University of Hong Kong, Shenzhen
Peng Li
Peng Li University of California, Santa Barbara
Sheng Chen
Sheng Chen University of Southampton
Feng Pan
Feng Pan Tsinghua University

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Best Scientists Citing Guoqi Li

Kaushik Roy

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Shimeng Yu

Shimeng Yu

Georgia Institute of Technology

Publications: 27

Jiangshuai Huang

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Publications: 25

Yuan Xie

Yuan Xie

Hong Kong University of Science and Technology

Publications: 21

Changyun Wen

Changyun Wen

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Publications: 19

Sheng Chen

Sheng Chen

University of Southampton

Publications: 16

Haizhou Li

Haizhou Li

Chinese University of Hong Kong, Shenzhen

Publications: 15

Su-Ting Han

Su-Ting Han

Shenzhen University

Publications: 13

Guang-Hong Yang

Guang-Hong Yang

Northeastern University

Publications: 13

Osvaldo Simeone

Osvaldo Simeone

Northeastern University

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Ye Zhou

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Shenzhen University

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Giacomo Indiveri

Giacomo Indiveri

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Publications: 12

Baochang Zhang

Baochang Zhang

Beihang University

Publications: 12

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