World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
38
Citations
6132
World Ranking
4906
National Ranking
724

Shaojun Wei publication distribution in Electronics and Electrical Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Electronics and Electrical Engineering in 2026. The highlighted bar marks where Shaojun Wei sits on this spectrum.

34–53 publications: 24 scientists 54–73 publications: 52 scientists 74–93 publications: 114 scientists 94–113 publications: 203 scientists 114–133 publications: 269 scientists 134–153 publications: 355 scientists 154–173 publications: 403 scientists 174–193 publications: 445 scientists 194–213 publications: 430 scientists 214–233 publications: 431 scientists 234–253 publications: 399 scientists 254–273 publications: 366 scientists 274–293 publications: 335 scientists 294–313 publications: 300 scientists 314–333 publications: 276 scientists 334–353 publications: 250 scientists 354–373 publications: 214 scientists 374–393 publications: 187 scientists 394–413 publications: 152 scientists 414–433 publications: 169 scientists 434–453 publications: 147 scientists 454–473 publications: 111 scientists 474–493 publications: 117 scientists 494–513 publications: 103 scientists 514–533 publications: 99 scientists 534–553 publications: 92 scientists 554–573 publications: 75 scientists 574–593 publications: 58 scientists 594–613 publications: 69 scientists 614–633 publications: 50 scientists 634–653 publications: 62 scientists 654–673 publications: 54 scientists 674–693 publications: 44 scientists 694–713 publications: 37 scientists 714–733 publications: 28 scientists 734–753 publications: 26 scientists 754–773 publications: 26 scientists 774–793 publications: 19 scientists 794–813 publications: 23 scientists 814–833 publications: 20 scientists 834–853 publications: 16 scientists 854–873 publications: 20 scientists 874–893 publications: 11 scientists 894–913 publications: 11 scientists 914–933 publications: 16 scientists 934–953 publications: 13 scientists 954–973 publications: 10 scientists 974–993 publications: 11 scientists 994–1,013 publications: 9 scientists 1,014–1,033 publications: 9 scientists 1,034–1,053 publications: 10 scientists 1,054–1,064 publications: 6 scientists 1,065+ publications: 99 scientists
34 publications 1,065+

This scientist: 427 publications — 78th percentile

78% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,065 publications or more.

Shaojun Wei D-index placement in Electronics and Electrical Engineering in 2026

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

30 D-Index: 178 scientists 31 D-Index: 257 scientists 32 D-Index: 263 scientists 33 D-Index: 262 scientists 34 D-Index: 244 scientists 35 D-Index: 236 scientists 36 D-Index: 211 scientists 37 D-Index: 220 scientists 38 D-Index: 214 scientists 39 D-Index: 214 scientists 40 D-Index: 205 scientists 41 D-Index: 187 scientists 42 D-Index: 194 scientists 43 D-Index: 201 scientists 44 D-Index: 155 scientists 45 D-Index: 189 scientists 46 D-Index: 148 scientists 47 D-Index: 160 scientists 48 D-Index: 134 scientists 49 D-Index: 130 scientists 50 D-Index: 141 scientists 51 D-Index: 156 scientists 52 D-Index: 108 scientists 53 D-Index: 130 scientists 54 D-Index: 112 scientists 55 D-Index: 97 scientists 56 D-Index: 111 scientists 57 D-Index: 102 scientists 58 D-Index: 108 scientists 59 D-Index: 120 scientists 60 D-Index: 103 scientists 61 D-Index: 93 scientists 62 D-Index: 92 scientists 63 D-Index: 74 scientists 64 D-Index: 77 scientists 65 D-Index: 73 scientists 66 D-Index: 64 scientists 67 D-Index: 69 scientists 68 D-Index: 60 scientists 69 D-Index: 39 scientists 70 D-Index: 57 scientists 71 D-Index: 59 scientists 72 D-Index: 46 scientists 73 D-Index: 49 scientists 74 D-Index: 38 scientists 75 D-Index: 35 scientists 76 D-Index: 32 scientists 77 D-Index: 35 scientists 78 D-Index: 31 scientists 79 D-Index: 22 scientists 80 D-Index: 34 scientists 81 D-Index: 31 scientists 82 D-Index: 34 scientists 83 D-Index: 23 scientists 84 D-Index: 18 scientists 85 D-Index: 30 scientists 86 D-Index: 19 scientists 87 D-Index: 19 scientists 88 D-Index: 20 scientists 89 D-Index: 8 scientists 90 D-Index: 17 scientists 91 D-Index: 7 scientists 92 D-Index: 14 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 12 scientists 97 D-Index: 10 scientists 98 D-Index: 10 scientists 99 D-Index: 12 scientists 100 D-Index: 16 scientists 101 D-Index: 5 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 8 scientists 105 D-Index: 9 scientists 106 D-Index: 13 scientists 107 D-Index: 4 scientists 108 D-Index: 5 scientists 109 D-Index: 10 scientists 110 D-Index: 8 scientists 111+ D-Index: 96 scientists
30 D-Index 111+

This scientist: 38 D-Index — 30th percentile

30% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 111 D-Index or more.

Overview

Shaojun Wei is affiliated with Tsinghua University in China and has contributed extensively to the fields of computer science and engineering. Their research spans numerous subfields including electrical and electronic engineering, artificial intelligence, hardware and architecture, computer vision and pattern recognition, and computer networks and communications.

The scientist's primary research topics include advanced memory and neural computing, ferroelectric and negative capacitance devices, parallel computing and optimization techniques, advanced neural network applications, embedded systems design techniques, coding theory and cryptography, and interconnection networks and systems.

Shaojun Wei has frequently published in several key venues, including:

  • IEEE Journal of Solid-State Circuits
  • IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
  • IEEE Transactions on Circuits and Systems I Regular Papers
  • IACR Transactions on Cryptographic Hardware and Embedded Systems
  • IEEE Transactions on Parallel and Distributed Systems

Notable recent publications illustrate the breadth and technical focus of their work:

  • "Highly Efficient Architecture of NewHope-NIST on FPGA using Low-Complexity NTT/INTT" (2020), published in IACR Transactions on Cryptographic Hardware and Embedded Systems
  • "A 28nm 29.2TFLOPS/W BF16 and 36.5TOPS/W INT8 Reconfigurable Digital CIM Processor with Unified FP/INT Pipeline and Bitwise In-Memory Booth Multiplication for Cloud Deep Learning Acceleration" (2022), presented at the 2022 IEEE International Solid-State Circuits Conference (ISSCC)
  • "LWRpro: An Energy-Efficient Configurable Crypto-Processor for Module-LWR" (2021), published in IEEE Transactions on Circuits and Systems I Regular Papers
  • "A Compact and High-Performance Hardware Architecture for CRYSTALS-Dilithium" (2021), published in IACR Transactions on Cryptographic Hardware and Embedded Systems
  • "ReDCIM: Reconfigurable Digital Computing-In-Memory Processor With Unified FP/INT Pipeline for Cloud AI Acceleration" (2022), published in IEEE Journal of Solid-State Circuits

The scientist has collaborated frequently with a set of co-authors, indicating an active network of research partnerships. Key collaborators include Leibo Liu, Shouyi Yin, Fengbin Tu, Jianfeng Zhu, and Yang Hu.

Best Publications

  • FP-BNN

    Shuang Liang;Shouyi Yin;Leibo Liu;Wayne Luk

  • A High Energy Efficient Reconfigurable Hybrid Neural Network Processor for Deep Learning Applications

    Shouyi Yin;Peng Ouyang;Shibin Tang;Fengbin Tu

  • A Survey of Coarse-Grained Reconfigurable Architecture and Design: Taxonomy, Challenges, and Applications

    Leibo Liu;Jianfeng Zhu;Zhaoshi Li;Yanan Lu

  • A Crop Monitoring System Based on Wireless Sensor Network

    Unknown

  • Highly Efficient Architecture of NewHope-NIST on FPGA using Low-Complexity NTT/INTT

    Neng Zhang;Bohan Yang;Chen Chen;Shouyi Yin

  • A 1.06-to-5.09 TOPS/W reconfigurable hybrid-neural-network processor for deep learning applications

    Shouyi Yin;Peng Ouyang;Shibin Tang;Fengbin Tu

  • A Multilevel Cell STT-MRAM-Based Computing In-Memory Accelerator for Binary Convolutional Neural Network

    Yu Pan;Peng Ouyang;Yinglin Zhao;Wang Kang

  • A 5.1pJ/Neuron 127.3us/Inference RNN-based Speech Recognition Processor using 16 Computing-in-Memory SRAM Macros in 65nm CMOS

    Ruiqi Guo;Yonggang Liu;Shixuan Zheng;Ssu-Yen Wu

  • Polyhedral model based mapping optimization of loop nests for CGRAs

    Dajiang Liu;Shouyi Yin;Leibo Liu;Shaojun Wei

  • RANA: towards efficient neural acceleration with refresh-optimized embedded DRAM

    Fengbin Tu;Weiwei Wu;Shouyi Yin;Leibo Liu

  • A Compact and High-Performance Hardware Architecture for CRYSTALS-Dilithium

    Cankun Zhao;Neng Zhang;Hanning Wang;Bohan Yang

  • A 141 UW, 2.46 PJ/Neuron Binarized Convolutional Neural Network Based Self-Learning Speech Recognition Processor in 28NM CMOS

    Shouyi Yin;Peng Ouyang;Shixuan Zheng;Dandan Song

  • LWRpro: An Energy-Efficient Configurable Crypto-Processor for Module-LWR

    Yihong Zhu;Min Zhu;Bohan Yang;Wenping Zhu

  • TranCIM: Full-Digital Bitline-Transpose CIM-based Sparse Transformer Accelerator With Pipeline/Parallel Reconfigurable Modes

    Unknown

  • 9.2A 28nm 12.1TOPS/W Dual-Mode CNN Processor Using Effective-Weight-Based Convolution and Error-Compensation-Based Prediction

    Huiyu Mo;Wenping Zhu;Wenjing Hu;Guangbin Wang

  • An Energy-Efficient Reconfigurable Processor for Binary-and Ternary-Weight Neural Networks With Flexible Data Bit Width

    Shouyi Yin;Peng Ouyang;Jianxun Yang;Tianyi Lu

  • Evolver: A Deep Learning Processor With On-Device Quantization–Voltage–Frequency Tuning

    Fengbin Tu;Weiwei Wu;Yang Wang;Hongjiang Chen

  • An Ultra-Low Power Binarized Convolutional Neural Network-Based Speech Recognition Processor With On-Chip Self-Learning

    Shixuan Zheng;Peng Ouyang;Dandan Song;Xiudong Li

  • Data-Flow Graph Mapping Optimization for CGRA With Deep Reinforcement Learning

    Dajiang Liu;Shouyi Yin;Guojie Luo;Jiaxing Shang

  • A High Throughput Acceleration for Hybrid Neural Networks With Efficient Resource Management on FPGA

    Shouyi Yin;Shibin Tang;Xinhan Lin;Peng Ouyang

  • An Efficient Application Mapping Approach for the Co-Optimization of Reliability, Energy, and Performance in Reconfigurable NoC Architectures

    Chen Wu;Chenchen Deng;Leibo Liu;Jie Han

  • Fast traffic sign recognition with a rotation invariant binary pattern based feature.

    Shouyi Yin;Peng Ouyang;Leibo Liu;Yike Guo

Frequent Co-Authors

Leibo Liu
Leibo Liu Tsinghua University
Shouyi Yin
Shouyi Yin Tsinghua University
Jie Han
Jie Han University of Alberta
Weisheng Zhao
Weisheng Zhao Beihang University
Youguang Zhang
Youguang Zhang Beihang University
Sheng Zhou
Sheng Zhou Tsinghua University
Meng-Fan Chang
Meng-Fan Chang National Tsing Hua University
Yuan Xie
Yuan Xie Hong Kong University of Science and Technology
Wang Kang
Wang Kang Beihang University
Yike Guo
Yike Guo Hong Kong Baptist University

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