World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
33
Citations
5070
World Ranking
6010
National Ranking
2010

Computer Science

D-Index
33
Citations
5052
World Ranking
12618
National Ranking
5110

Zhengya Zhang 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 Zhengya Zhang 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: 119 publications — 7th percentile

7% of scientists in this discipline score the same or lower.

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

Zhengya Zhang 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 Zhengya Zhang 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: 33 D-Index — 14th percentile

14% of scientists in this discipline score the same or lower.

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

Overview

Zhengya Zhang is a researcher affiliated with the University of Michigan-Ann Arbor in the United States. Their body of work spans multiple fields within engineering and computer science, with a focus on electrical and electronic engineering as well as several related subfields.

The main fields of study Zhang has contributed to include:

  • Engineering
  • Computer Science

Within these broad fields, their work engages with specialized subfields such as:

  • Electrical and Electronic Engineering
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications
  • Biomedical Engineering
  • Hardware and Architecture

Zhang's research topics cover areas including:

  • Advanced Memory and Neural Computing
  • CCD and CMOS Imaging Sensors
  • Advanced Neural Network Applications
  • Error Correcting Code Techniques
  • Advanced Wireless Communication Techniques
  • Ferroelectric and Negative Capacitance Devices
  • Parallel Computing and Optimization Techniques

Their work is published frequently in established venues such as:

  • IEEE Journal of Solid-State Circuits
  • arXiv (Cornell University)
  • 2022 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits)
  • IEEE Transactions on Circuits and Systems I Regular Papers
  • Scientific Reports

Recent papers authored or co-authored by Zhengya Zhang include:

  • "SNAP: An Efficient Sparse Neural Acceleration Processor for Unstructured Sparse Deep Neural Network Inference" (2020), published in IEEE Journal of Solid-State Circuits
  • "A Configurable Successive-Cancellation List Polar Decoder Using Split-Tree Architecture" (2020), published in IEEE Journal of Solid-State Circuits
  • "An 8-bit 20.7 TOPS/W Multi-Level Cell ReRAM-based Compute Engine" (2022), published in 2022 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits)
  • "A Fully Integrated Reprogrammable CMOS-RRAM Compute-in-Memory Coprocessor for Neuromorphic Applications" (2020), published in IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
  • "A 1.87-mm2 56.9-GOPS Accelerator for Solving Partial Differential Equations" (2020), published in IEEE Journal of Solid-State Circuits

Their frequent co-authors include:

  • Wei Tang
  • Yaoyu Tao
  • Michael P. Flynn
  • Wei Lü
  • Zhang Jie-Fang

Best Publications

  • A fully integrated reprogrammable memristor–CMOS system for efficient multiply–accumulate operations

    Fuxi Cai;Justin M. Correll;Seung Hwan Lee;Yong Lim;Yong Lim

  • Sparse coding with Memristor networks

    Wei Lu;Fuxi Cai;Patrick Sheridan;Chao Du

  • An Efficient 10GBASE-T Ethernet LDPC Decoder Design With Low Error Floors

    Zhengya Zhang;V. Anantharam;M.J. Wainwright;B. Nikolic

  • Analysis of Absorbing Sets and Fully Absorbing Sets of Array-Based LDPC Codes

    L. Dolecek;Zhengya Zhang;V. Anantharam;M.J. Wainwright

  • An Injectable 64 nW ECG Mixed-Signal SoC in 65 nm for Arrhythmia Monitoring

    Yen-Po Chen;Dongsuk Jeon;Yoonmyung Lee;Yejoong Kim

  • Design of LDPC decoders for improved low error rate performance: quantization and algorithm choices

    Zhengya Zhang;L. Dolecek;B. Nikolic;V. Anantharam

  • A Native Stochastic Computing Architecture Enabled by Memristors

    Phil Knag;Wei Lu;Zhengya Zhang

  • GEN03-6: Investigation of Error Floors of Structured Low-Density Parity-Check Codes by Hardware Emulation

    Zhengya Zhang;Lara Dolecek;Borivoje Nikolic;Venkat Anantharam

  • Lowering LDPC Error Floors by Postprocessing

    Zhengya Zhang;L. Dolecek;B. Nikolic;V. Anantharam

  • A 640M pixel/s 3.65mW sparse event-driven neuromorphic object recognition processor with on-chip learning

    Jung Kuk Kim;Phil Knag;Thomas Chen;Zhengya Zhang

  • Analysis of Absorbing Sets for Array-Based LDPC Codes

    L. Dolecek;Zhengya Zhang;V. Anantharam;M. Wainwright

  • A 4.68Gb/s belief propagation polar decoder with bit-splitting register file

    Youn Sung Park;Yaoyu Tao;Shuanghong Sun;Zhengya Zhang

  • Predicting error floors of structured LDPC codes: deterministic bounds and estimates

    L. Dolecek;P. Lee;Zhengya Zhang;V. Anantharam

  • Low-Power High-Throughput LDPC Decoder Using Non-Refresh Embedded DRAM

    Youn Sung Park;David Blaauw;Dennis Sylvester;Zhengya Zhang

  • A Sparse Coding Neural Network ASIC With On-Chip Learning for Feature Extraction and Encoding

    Phil Knag;Jung Kuk Kim;Thomas Chen;Zhengya Zhang

  • 24.3 An implantable 64nW ECG-monitoring mixed-signal SoC for arrhythmia diagnosis

    Dongsuk Jeon;Yen-Po Chen;Yoonmyung Lee;Yejoong Kim

  • SNAP: An Efficient Sparse Neural Acceleration Processor for Unstructured Sparse Deep Neural Network Inference

    Jie-Fang Zhang;Ching-En Lee;Chester Liu;Yakun Sophia Shao

  • CASCADE: Connecting RRAMs to Extend Analog Dataflow In An End-To-End In-Memory Processing Paradigm

    Teyuh Chou;Wei Tang;Jacob Botimer;Zhengya Zhang

  • Evaluation of the Low Frame Error Rate Performance of LDPC Codes Using Importance Sampling

    L. Dolecek;Zhengya Zhang;M. Wainwright;V. Anantharam

  • Quantization Effects in Low-Density Parity-Check Decoders

    Zhengya Zhang;L. Dolecek;M. Wainwright;V. Anantharam

  • A 3.43TOPS/W 48.9pJ/pixel 50.1nJ/classification 512 analog neuron sparse coding neural network with on-chip learning and classification in 40nm CMOS

    Fred N. Buhler;Peter Brown;Jiabo Li;Thomas Chen

  • Memristive devices for stochastic computing

    Siddharth Gaba;Phil Knag;Zhengya Zhang;Wei Lu

Frequent Co-Authors

Lara Dolecek
Lara Dolecek University of California, Los Angeles
Borivoje Nikolic
Borivoje Nikolic University of California, Berkeley
Venkat Anantharam
Venkat Anantharam University of California, Berkeley
Wei Lu
Wei Lu University of Michigan–Ann Arbor
David Blaauw
David Blaauw University of Michigan–Ann Arbor
Dennis Sylvester
Dennis Sylvester University of Michigan–Ann Arbor
Marios C. Papaefthymiou
Marios C. Papaefthymiou University of California, Irvine
Michael P. Flynn
Michael P. Flynn University of Michigan–Ann Arbor
Richard D. Wesel
Richard D. Wesel University of California, Los Angeles

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