World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
55
Citations
10966
World Ranking
2197
National Ranking
857

Sarma Vrudhula 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 Sarma Vrudhula 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: 239 publications — 41st percentile

41% of scientists in this discipline score the same or lower.

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

Sarma Vrudhula 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 Sarma Vrudhula 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: 55 D-Index — 69th percentile

69% 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

  • 2016 - IEEE Fellow For contributions to low-power and energy-efficient design of digital circuits and systems

Overview

Sarma Vrudhula is affiliated with Arizona State University in the United States and has contributed extensively to the fields of engineering and computer science. Their research focuses on multiple subfields, including electrical and electronic engineering, computer vision and pattern recognition, artificial intelligence, hardware and architecture, and biomedical engineering.

The scientist's work covers a broad range of topics, notably advanced memory and neural computing, advanced neural network applications, ferroelectric and negative capacitance devices, advancements in semiconductor devices and circuit design, CCD and CMOS imaging sensors, semiconductor materials and devices, and parallel computing and optimization techniques.

Some of the recent papers by Sarma Vrudhula include the following:

  • ELSA, 2020, ACM Transactions on Embedded Computing Systems
  • A Novel ASIC Design Flow Using Weight-Tunable Binary Neurons as Standard Cells, 2022, IEEE Transactions on Circuits and Systems I Regular Papers
  • Heterogeneous FPGA Architecture Using Threshold Logic Gates for Improved Area, Power, and Performance, 2021, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
  • A Flash-based Current-mode IC to Realize Quantized Neural Networks, 2022, 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE)
  • EdgeWise: Energy-efficient CNN Computation on Edge Devices under Stochastic Communication Delays, 2022, ACM Transactions on Embedded Computing Systems

Frequent co-authors collaborating with Sarma Vrudhula include:

  • Ankit Wagle
  • Gian Singh
  • Sunil P. Khatri
  • Mehdi Ghasemi
  • Carole-Jean Wu

Publishing venues often chosen by Sarma Vrudhula for disseminating research comprise:

  • arXiv (Cornell University)
  • IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
  • ACM Transactions on Embedded Computing Systems
  • IEEE Transactions on Circuits and Systems I Regular Papers
  • IEEE Transactions on Computers

In recognition of contributions to the field, Sarma Vrudhula was honored as an IEEE Fellow in 2016 for work related to low-power and energy-efficient design of digital circuits and systems.

Best Publications

  • Throughput-Optimized OpenCL-based FPGA Accelerator for Large-Scale Convolutional Neural Networks

    Naveen Suda;Vikas Chandra;Ganesh Dasika;Abinash Mohanty

  • Battery modeling for energy aware system design

    R. Rao;S. Vrudhula;D.N. Rakhmatov

  • Predictive Modeling of the NBTI Effect for Reliable Design

    S. Bhardwaj;Wenping Wang;R. Vattikonda;Y. Cao

  • Optimizing Loop Operation and Dataflow in FPGA Acceleration of Deep Convolutional Neural Networks

    Yufei Ma;Yu Cao;Sarma Vrudhula;Jae-sun Seo

  • An analytical high-level battery model for use in energy management of portable electronic systems

    Daler N. Rakhmatov;Sarma B. K. Vrudhula

  • The Impact of NBTI Effect on Combinational Circuit: Modeling, Simulation, and Analysis

    Wenping Wang;Shengqi Yang;S. Bhardwaj;S. Vrudhula

  • Energy management for battery-powered embedded systems

    Daler Rakhmatov;Sarma Vrudhula

  • Optimizing the Convolution Operation to Accelerate Deep Neural Networks on FPGA

    Yufei Ma;Yu Cao;Sarma Vrudhula;Jae-sun Seo

  • A model for battery lifetime analysis for organizing applications on a pocket computer

    D. Rakhmatov;S. Vrudhula;D.A. Wallach

  • The impact of NBTI on the performance of combinational and sequential circuits

    Wenping Wang;Shengqi Yang;Sarvesh Bhardwaj;Rakesh Vattikonda

  • BDD Based Decomposition of Logic Functions with Application to FPGA Synthesis

    Yung-Te Lai;Massoud Pedram;Sarma B. K. Vrudhula

  • Scalable and modularized RTL compilation of Convolutional Neural Networks onto FPGA

    Yufei Ma;Naveen Suda;Yu Cao;Jae-sun Seo

  • EVBDD-based algorithms for integer linear programming, spectral transformation, and function decomposition

    Y.-T. Lai;M. Pedram;S.B.K. Vrudhula

  • EPIMap: using epimorphism to map applications on CGRAs

    Mahdi Hamzeh;Aviral Shrivastava;Sarma Vrudhula

  • Fully parallel write/read in resistive synaptic array for accelerating on-chip learning.

    Ligang Gao;I-Ting Wang;Pai-Yu Chen;Sarma Vrudhula

  • Energy-Efficient Operation of Multicore Processors by DVFS, Task Migration, and Active Cooling

    Vinay Hanumaiah;Sarma Vrudhula

  • Power balanced coverage-time optimization for clustered wireless sensor networks

    Tao Shu;Marwan Krunz;Sarma Vrudhula

  • Mitigating Effects of Non-ideal Synaptic Device Characteristics for On-chip Learning

    Pai-Yu Chen;Binbin Lin;I-Ting Wang;Tuo-Hung Hou

  • An automatic RTL compiler for high-throughput FPGA implementation of diverse deep convolutional neural networks

    Yufei Ma;Yu Cao;Sarma Vrudhula;Jae-sun Seo

  • Static power optimization of deep submicron CMOS circuits for dual V/sub T/ technology

    Qi Wang;Sarma B. K. Vrudhula

Frequent Co-Authors

Yu Cao
Yu Cao University of Minnesota
Jae-sun Seo
Jae-sun Seo Cornell University
David Blaauw
David Blaauw University of Michigan–Ann Arbor
Shimeng Yu
Shimeng Yu Georgia Institute of Technology
Chaitali Chakrabarti
Chaitali Chakrabarti Arizona State University
Pai-Yu Chen
Pai-Yu Chen Arizona State University
Jieping Ye
Jieping Ye Alibaba Group (China)
Naehyuck Chang
Naehyuck Chang Korea Advanced Institute of Science and Technology
Vladimir Zolotov
Vladimir Zolotov IBM (United States)
Michael N. Kozicki
Michael N. Kozicki Arizona State University

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