World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
50
Citations
11286
World Ranking
2775
National Ranking
1056

Computer Science

D-Index
52
Citations
11922
World Ranking
5047
National Ranking
2347

Magdy Bayoumi 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 Magdy Bayoumi 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: 673 publications — 93rd percentile

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

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

Magdy Bayoumi 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 Magdy Bayoumi 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: 50 D-Index — 60th percentile

60% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 1999 - IEEE Fellow For contributions to application specific digital signal processing architectures and computer arithmetic.

Overview

Magdy Bayoumi is affiliated with the University of Louisiana at Lafayette in the United States. Their research portfolio spans multiple areas within computer science and engineering, with a significant focus on computer vision, artificial intelligence, and hardware architecture.

The main fields of study for their work include:

  • Computer Science
  • Engineering

Their subfields of study cover specialized domains such as:

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

Key topics addressed in their research publications are:

  • Image and Video Quality Assessment
  • Advanced Memory and Neural Computing
  • Integrated Circuits and Semiconductor Failure Analysis
  • Physical Unclonable Functions (PUFs) and Hardware Security
  • Neural Networks and Applications
  • Neuroscience and Neural Engineering
  • Video Coding and Compression Technologies

Their recent papers reflect a diverse range of interests within computational and electronic systems, including:

  • "A Deep Learning Approach for Automatic Seizure Detection in Children With Epilepsy," 2021, Frontiers in Computational Neuroscience
  • "A survey on security in internet of things with a focus on the impact of emerging technologies," 2022, Internet of Things
  • "Machine Learning-Based Approach for Hardware Faults Prediction," 2020, IEEE Transactions on Circuits and Systems I Regular Papers
  • "Assessment of a Spatiotemporal Deep Learning Approach for Soil Moisture Prediction and Filling the Gaps in Between Soil Moisture Observations," 2021, Frontiers in Artificial Intelligence
  • "Designing Novel AAD Pooling in Hardware for a Convolutional Neural Network Accelerator," 2022, IEEE Transactions on Very Large Scale Integration (VLSI) Systems

Frequently publishing in venues such as:

  • arXiv (Cornell University)
  • Cluster Computing
  • 2022 IEEE International Symposium on Circuits and Systems (ISCAS)
  • Internet of Things
  • IEEE Transactions on Circuits and Systems I Regular Papers

They have collaborated repeatedly with co-authors including:

  • Kasem Khalil
  • Ashok Kumar
  • Mahmoud Darwich
  • Bappaditya Dey
  • Zag ElSayed

In recognition of their professional contributions, Magdy Bayoumi was awarded the IEEE Fellow distinction in 1999 for contributions to application specific digital signal processing architectures and computer arithmetic.

Best Publications

  • Performance analysis of low-power 1-bit CMOS full adder cells

    A.M. Shams;T.K. Darwish;M.A. Bayoumi

  • Design of Robust, Energy-Efficient Full Adders for Deep-Submicrometer Design Using Hybrid-CMOS Logic Style

    S. Goel;A. Kumar;M.A. Bayoumi

  • Efficient Epileptic Seizure Prediction Based on Deep Learning

    Hisham Daoud;Magdy A. Bayoumi

  • High-performance and low-power conditional discharge flip-flop

    Peiyi Zhao;T.K. Darwish;M.A. Bayoumi

  • A novel high-performance CMOS 1-bit full-adder cell

    A.M. Shams;M.A. Bayoumi

  • Low-Power Cache Design Using 7T SRAM Cell

    R.E. Aly;M.A. Bayoumi

  • A survey on security in internet of things with a focus on the impact of emerging technologies

    Unknown

  • The hierarchical hypercube: a new interconnection topology for massively parallel systems

    Q.M. Malluhi;M.A. Bayoumi

  • A VLSI implementation of residue adders

    M. Bayoumi;G. Jullien;W. Miller

  • A new cell for low power adders

    E. Abu-Shama;M. Bayoumi

  • A Deep Learning Approach for Automatic Seizure Detection in Children With Epilepsy.

    Ahmed M. Abdelhameed;Magdy A. Bayoumi

  • Design methodologies for high-performance noise-tolerant XOR-XNOR circuits

    S. Goel;M.A. Elgamel;M.A. Bayoumi;Y. Hanafy

  • NEDA: a low-power high-performance DCT architecture

    A.M. Shams;A. Chidanandan;W. Pan;M.A. Bayoumi

  • Low-Power Clock Branch Sharing Double-Edge Triggered Flip-Flop

    Peiyi Zhao;J. McNeely;P. Golconda;M.A. Bayoumi

  • A low power 10-transistor full adder cell for embedded architectures

    A.A. Fayed;M.A. Bayoumi

  • Discrete Wavelet Transform: Architectures, Design and Performance Issues

    Michael Weeks;Magdy Bayoumi

  • Fast Motion Estimation System Using Dynamic Models for H.264/AVC Video Coding

    Y. Ismail;J. B. McNeely;M. Shaaban;H. Mahmoud

  • Lightweight Cryptography for Internet of Insecure Things: A Survey

    Indira Kalyan Dutta;Bhaskar Ghosh;Magdy Bayoumi

  • Data Fusion in WSN

    Ahmed Abdelgawad;Magdy Bayoumi

  • Fast and flexible architectures for RNS arithmetic decoding

    K.M. Elleithy;M.A. Bayoumi

  • Learning on Silicon: Adaptive VLSI Neural Systems

    Magdy A. Bayoumi;Gert Cauwenberghs

  • Machine Learning-Based Approach for Hardware Faults Prediction

    Kasem Khalil;Omar Eldash;Ashok Kumar;Magdy Bayoumi

  • Interconnect noise analysis and optimization in deep submicron technology

    M.A. Elgamel;M.A. Bayoumi

Frequent Co-Authors

Hongyi Wu
Hongyi Wu University of Arizona
Gert Cauwenberghs
Gert Cauwenberghs University of California, San Diego
Rajkumar Buyya
Rajkumar Buyya University of Melbourne
Ram Krishnamurthy
Ram Krishnamurthy Intel (United States)
Mircea R. Stan
Mircea R. Stan University of Virginia
Yong Lian
Yong Lian York University
Massimo Alioto
Massimo Alioto National University of Singapore
Edgar Sanchez-Sinencio
Edgar Sanchez-Sinencio Texas A&M University
Farinaz Koushanfar
Farinaz Koushanfar University of California, San Diego
Yen-Kuang Chen
Yen-Kuang Chen Alibaba Group (China)

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