World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
47
Citations
11755
World Ranking
4746
National Ranking
927

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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