World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
30
Citations
5442
World Ranking
13931
National Ranking
5539

R. Iris Bahar publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where R. Iris Bahar sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 152 publications — 28th percentile

28% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

R. Iris Bahar D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where R. Iris Bahar sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 30 D-Index — 3rd percentile

3% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

R. Iris Bahar is affiliated with Brown University in the United States and has a research focus spanning computer science and engineering with a particular emphasis on electrical and electronic engineering, computer vision and pattern recognition, artificial intelligence, hardware and architecture, and aerospace engineering. Their work covers a broad range of fields that include both theoretical and applied aspects of these disciplines.

The scientist's recent publications demonstrate active engagement in topics such as advanced neural network applications, parallel computing and optimization techniques, low-power high-performance VLSI design, semiconductor materials and devices, robotics and sensor-based localization, advancements in semiconductor devices and circuit design, and advanced image and video retrieval techniques.

Recent papers authored or coauthored by R. Iris Bahar include:

  • Workshops on Extreme Scale Design Automation (ESDA) Challenges and Opportunities for 2025 and Beyond, 2020, arXiv (Cornell University)
  • Fundamental Thermal Limits on Data Retention in Low-Voltage CMOS Latches and SRAM, 2020, IEEE Transactions on Device and Materials Reliability
  • A Reconfigurable Hardware Library for Robot Scene Perception, 2022, Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design
  • Hardware Acceleration of Monte-Carlo Sampling for Energy Efficient Robust Robot Manipulation, 2020, arXiv (Cornell University)
  • Voltage Noise Mitigation With Barrier Approximation, 2020, IEEE Computer Architecture Letters

Frequent coauthors include:

  • Yanqi Liu
  • K. Semir Tatlidil
  • Steven A. Sloman
  • Elahe Rezaei
  • Marco Donato

Their work has been published primarily in venues such as:

  • arXiv (Cornell University)
  • IEEE Computer Architecture Letters
  • IEEE Transactions on Device and Materials Reliability
  • Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design
  • 2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)

Best Publications

  • Algebric Decision Diagrams and Their Applications

    R. I. Bahar;E. A. Frohm;C. M. Gaona;G. D. Hachtel

  • Algebraic decision diagrams and their applications

    R. Iris Bahar;Erica A. Frohm;Charles M. Gaona;Gary D. Hachtel

  • Power and energy reduction via pipeline balancing

    R. Iris Bahar;Srilatha Manne

  • DRUM: A Dynamic Range Unbiased Multiplier for Approximate Applications

    Soheil Hashemi;R. Iris Bahar;Sherief Reda

  • ABACUS: a technique for automated behavioral synthesis of approximate computing circuits

    Kumud Nepal;Yueting Li;R. Iris Bahar;Sherief Reda

  • Power and performance tradeoffs using various caching strategies

    R. Iris Bahar;Gianluca Albera;Srilatha Manne

  • A Probabilistic-Based Design Methodology for Nanoscale Computation

    R. Iris Bahar;Joseph Mundy;Jie Chen

  • Understanding the impact of precision quantization on the accuracy and energy of neural networks

    Soheil Hashemi;Nicholas Anthony;Hokchhay Tann;R. Iris Bahar

  • Architectures for silicon nanoelectronics and beyond

    R.I. Bahar;C. Lau;D. Hammerstrom;D. Marculescu

  • Designing logic circuits for probabilistic computation in the presence of noise

    K. Nepal;R. I. Bahar;J. Mundy;W. R. Patterson

  • Dynamically reconfiguring processor resources to reduce power consumption in high-performance processors

    Roberto Maro;Yu Bai;R. Iris Bahar

  • Runtime configurable deep neural networks for energy-accuracy trade-off

    Hokchhay Tann;Soheil Hashemi;R. Iris Bahar;Sherief Reda

  • Automated High-Level Generation of Low-Power Approximate Computing Circuits

    Kumud Nepal;Soheil Hashemi;Hokchhay Tann;R. Iris Bahar

  • Hardware-Software Codesign of Accurate, Multiplier-free Deep Neural Networks

    Hokchhay Tann;Soheil Hashemi;R. Iris Bahar;Sherief Reda

  • Nano, Quantum and Molecular Computing: Implications to High Level Design and Validation

    Sandeep K. Shukla;R. Iris Bahar

  • A symbolic method to reduce power consumption of circuits containing false paths

    R. Iris Bahar;Gary D. Hachtel;Enrico Macii;Fabio Somenzi

  • Parametric yield management for 3D ICs: Models and strategies for improvement

    Cesare Ferri;Sherief Reda;R. Iris Bahar

  • Embedded-TM: Energy and complexity-effective hardware transactional memory for embedded multicore systems

    Cesare Ferri;Samantha Wood;Tali Moreshet;R. Iris Bahar

  • Energy reduction in multiprocessor systems using transactional memory

    Tali Moreshet;R. Iris Bahar;Maurice Herlihy

  • A low-power dynamic divider for approximate applications

    Soheil Hashemi;R. Iris Bahar;Sherief Reda

  • Computing the Maximum Power Cycles of a Sequential Circuit

    Srilatha Manne;Abelardo Pardo;R. Iris Bahar;Gary D. Hachtel

Frequent Co-Authors

Sherief Reda
Sherief Reda Brown University
Maurice Herlihy
Maurice Herlihy Brown University
Luca Benini
Luca Benini ETH Zurich
Enrico Macii
Enrico Macii Polytechnic University of Turin
Massimo Poncino
Massimo Poncino Polytechnic University of Turin
Joseph L. Mundy
Joseph L. Mundy Brown University
Sandeep K. Shukla
Sandeep K. Shukla International Institute of Information Technology, Hyderabad
Fabio Somenzi
Fabio Somenzi University of Colorado Boulder
Gary D. Hachtel
Gary D. Hachtel University of Colorado Boulder
David Z. Pan
David Z. Pan The University of Texas at Austin

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