World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
81
Citations
31726
World Ranking
480
National Ranking
220

Shimeng Yu 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 Shimeng Yu 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: 358 publications — 68th percentile

68% of scientists in this discipline score the same or lower.

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

Shimeng Yu 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 Shimeng Yu 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: 81 D-Index — 93rd percentile

93% of scientists in this discipline score the same or lower.

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

Overview

Shimeng Yu is affiliated with the Georgia Institute of Technology in the United States. Their research primarily focuses on engineering, with a specialization in electrical and electronic engineering. They have contributed extensively to the study and development of semiconductor materials and devices, advanced memory technologies, and neural computing systems.

The scientist's work covers several subfields, including materials chemistry, artificial intelligence, cellular and molecular neuroscience, and computer vision and pattern recognition. Their main research topics are:

  • Ferroelectric and Negative Capacitance Devices
  • Advanced Memory and Neural Computing
  • Semiconductor materials and devices
  • Ferroelectric and Piezoelectric Materials
  • Advancements in Semiconductor Devices and Circuit Design
  • Neuroscience and Neural Engineering
  • MXene and MAX Phase Materials

Shimeng Yu has published in a range of specialized venues. Frequent publication outlets include:

  • IEEE Transactions on Electron Devices
  • arXiv (Cornell University)
  • IEEE Electron Device Letters
  • IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
  • IEEE Transactions on Very Large Scale Integration (VLSI) Systems

The scientist collaborates regularly with a set of frequent coauthors. The most common collaborators are:

  • Asif Islam Khan
  • Suman Datta
  • Jae Hur
  • Yuan-Chun Luo
  • Anni Lu

Recent papers by Shimeng Yu illustrate a focus on neuromorphic computing, in-memory computing, and compute-in-memory architectures for machine learning. Notable publications include:

  • "Neuro-inspired computing chips," 2020, Nature Electronics
  • "Power-efficient combinatorial optimization using intrinsic noise in memristor Hopfield neural networks," 2020, Nature Electronics
  • "Compute-in-Memory Chips for Deep Learning: Recent Trends and Prospects," 2021, IEEE Circuits and Systems Magazine
  • "DNN+NeuroSim V2.0: An End-to-End Benchmarking Framework for Compute-in-Memory Accelerators for On-Chip Training," 2020, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
  • "High-Throughput In-Memory Computing for Binary Deep Neural Networks With Monolithically Integrated RRAM and 90-nm CMOS," 2020, IEEE Transactions on Electron Devices

Best Publications

  • Metal–Oxide RRAM

    H-S P. Wong;Heng-Yuan Lee;Shimeng Yu;Yu-Sheng Chen

  • Synaptic electronics: materials, devices and applications

    Duygu Kuzum;Duygu Kuzum;Shimeng Yu;Shimeng Yu;H-S Philip Wong

  • Optoelectronic resistive random access memory for neuromorphic vision sensors.

    Feichi Zhou;Zheng Zhou;Jiewei Chen;Tsz Hin Choy

  • Neuro-Inspired Computing With Emerging Nonvolatile Memorys

    Shimeng Yu

  • An Electronic Synapse Device Based on Metal Oxide Resistive Switching Memory for Neuromorphic Computation

    Shimeng Yu;Yi Wu;R. Jeyasingh;D. Kuzum

  • Neuro-inspired computing chips

    Wenqiang Zhang;Bin Gao;Jianshi Tang;Peng Yao

  • SiGe epitaxial memory for neuromorphic computing with reproducible high performance based on engineered dislocations

    Shinhyun Choi;Scott H. Tan;Zefan Li;Yunjo Kim

  • NeuroSim: A Circuit-Level Macro Model for Benchmarking Neuro-Inspired Architectures in Online Learning

    Pai-Yu Chen;Xiaochen Peng;Shimeng Yu

  • Emerging Memory Technologies: Recent Trends and Prospects

    Shimeng Yu;Pai-Yu Chen

  • Ferroelectric FET analog synapse for acceleration of deep neural network training

    Matthew Jerry;Pai-Yu Chen;Jianchi Zhang;Pankaj Sharma

  • A Low Energy Oxide‐Based Electronic Synaptic Device for Neuromorphic Visual Systems with Tolerance to Device Variation

    Shimeng Yu;Bin Gao;Zheng Fang;Hongyu Yu

  • Conduction mechanism of TiN/HfOx/Pt resistive switching memory: A trap-assisted-tunneling model

    Shimeng Yu;Ximeng Guan;H.-S. Philip Wong

  • NeuroSim+: An integrated device-to-algorithm framework for benchmarking synaptic devices and array architectures

    Pai-Yu Chen;Xiaochen Peng;Shimeng Yu

  • HfOx-based vertical resistive switching random access memory suitable for bit-cost-effective three-dimensional cross-point architecture.

    Shimeng Yu;Hong Yu Chen;Bin Gao;Jinfeng Kang

  • On the Switching Parameter Variation of Metal-Oxide RRAM—Part I: Physical Modeling and Simulation Methodology

    Ximeng Guan;Shimeng Yu;H.-S Philip Wong

  • Power-efficient combinatorial optimization using intrinsic noise in memristor Hopfield neural networks

    Fuxi Cai;Fuxi Cai;Suhas Kumar;Thomas Van Vaerenbergh;Xia Sheng

  • Overcoming the challenges of crossbar resistive memory architectures

    Cong Xu;Dimin Niu;Naveen Muralimanohar;Rajeev Balasubramonian

  • Investigating the switching dynamics and multilevel capability of bipolar metal oxide resistive switching memory

    Shimeng Yu;Yi Wu;H.-S. Philip Wong

  • Compact Modeling of RRAM Devices and Its Applications in 1T1R and 1S1R Array Design

    Pai-Yu Chen;Shimeng Yu

  • DNN+NeuroSim: An End-to-End Benchmarking Framework for Compute-in-Memory Accelerators with Versatile Device Technologies

    Xiaochen Peng;Shanshi Huang;Yandong Luo;Xiaoyu Sun

  • HfOx based vertical resistive random access memory for cost-effective 3D cross-point architecture without cell selector

    Hong-Yu Chen;Shimeng Yu;Bin Gao;Peng Huang

  • A SPICE Compact Model of Metal Oxide Resistive Switching Memory With Variations

    Ximeng Guan;Shimeng Yu;H-S P. Wong

Frequent Co-Authors

H.-S. Philip Wong
H.-S. Philip Wong Stanford University
Pai-Yu Chen
Pai-Yu Chen Arizona State University
Bin Gao
Bin Gao Xi'an Jiaotong University
Jinfeng Kang
Jinfeng Kang Peking University
Jae-sun Seo
Jae-sun Seo Cornell University
Yu Cao
Yu Cao University of Minnesota
Huaqiang Wu
Huaqiang Wu Tsinghua University
Sarma Vrudhula
Sarma Vrudhula Arizona State University
He Qian
He Qian Tsinghua University
Asif Islam Khan
Asif Islam Khan Georgia Institute of Technology

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