World's Best Scientists 2026 revealed!
Michael A. Guillorn

Michael A. Guillorn

D-Index & Metrics

Materials Science

D-Index
42
Citations
7126
World Ranking
12542
National Ranking
2874

Michael A. Guillorn publication distribution in Materials Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Materials Science in 2026. The highlighted bar marks where Michael A. Guillorn sits on this spectrum.

50–69 publications: 28 scientists 70–89 publications: 152 scientists 90–109 publications: 356 scientists 110–129 publications: 487 scientists 130–149 publications: 723 scientists 150–169 publications: 835 scientists 170–189 publications: 850 scientists 190–209 publications: 891 scientists 210–229 publications: 862 scientists 230–249 publications: 766 scientists 250–269 publications: 726 scientists 270–289 publications: 665 scientists 290–309 publications: 593 scientists 310–329 publications: 537 scientists 330–349 publications: 477 scientists 350–369 publications: 440 scientists 370–389 publications: 356 scientists 390–409 publications: 321 scientists 410–429 publications: 256 scientists 430–449 publications: 246 scientists 450–469 publications: 216 scientists 470–489 publications: 212 scientists 490–509 publications: 174 scientists 510–529 publications: 194 scientists 530–549 publications: 162 scientists 550–569 publications: 131 scientists 570–589 publications: 111 scientists 590–609 publications: 103 scientists 610–629 publications: 99 scientists 630–649 publications: 77 scientists 650–669 publications: 92 scientists 670–689 publications: 56 scientists 690–709 publications: 53 scientists 710–729 publications: 53 scientists 730–749 publications: 38 scientists 750–769 publications: 52 scientists 770–789 publications: 43 scientists 790–809 publications: 38 scientists 810–829 publications: 34 scientists 830–849 publications: 25 scientists 850–869 publications: 18 scientists 870–889 publications: 20 scientists 890–909 publications: 24 scientists 910–929 publications: 27 scientists 930–949 publications: 20 scientists 950–969 publications: 17 scientists 970–989 publications: 10 scientists 990–1,009 publications: 16 scientists 1,010–1,029 publications: 13 scientists 1,030–1,049 publications: 12 scientists 1,050–1,069 publications: 9 scientists 1,070–1,089 publications: 8 scientists 1,090–1,109 publications: 7 scientists 1,110–1,129 publications: 9 scientists 1,130–1,149 publications: 2 scientists 1,150–1,162 publications: 5 scientists 1,163+ publications: 100 scientists
50 publications 1,163+

This scientist: 119 publications — 6th percentile

6% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,163 publications or more.

Michael A. Guillorn D-index placement in Materials Science in 2026

The chart shows the D-index (discipline H-index) distribution of Materials Science scientists ranked by Research.com in 2026. The highlighted bar marks where Michael A. Guillorn sits on this spectrum.

40–41 D-Index: 211 scientists 42–43 D-Index: 450 scientists 44–45 D-Index: 612 scientists 46–47 D-Index: 612 scientists 48–49 D-Index: 598 scientists 50–51 D-Index: 657 scientists 52–53 D-Index: 667 scientists 54–55 D-Index: 621 scientists 56–57 D-Index: 597 scientists 58–59 D-Index: 610 scientists 60–61 D-Index: 587 scientists 62–63 D-Index: 606 scientists 64–65 D-Index: 533 scientists 66–67 D-Index: 490 scientists 68–69 D-Index: 469 scientists 70–71 D-Index: 378 scientists 72–73 D-Index: 421 scientists 74–75 D-Index: 359 scientists 76–77 D-Index: 323 scientists 78–79 D-Index: 299 scientists 80–81 D-Index: 230 scientists 82–83 D-Index: 210 scientists 84–85 D-Index: 195 scientists 86–87 D-Index: 203 scientists 88–89 D-Index: 175 scientists 90–91 D-Index: 175 scientists 92–93 D-Index: 142 scientists 94–95 D-Index: 121 scientists 96–97 D-Index: 117 scientists 98–99 D-Index: 107 scientists 100–101 D-Index: 88 scientists 102–103 D-Index: 85 scientists 104–105 D-Index: 68 scientists 106–107 D-Index: 62 scientists 108–109 D-Index: 57 scientists 110–111 D-Index: 45 scientists 112–113 D-Index: 49 scientists 114–115 D-Index: 50 scientists 116–117 D-Index: 34 scientists 118–119 D-Index: 38 scientists 120–121 D-Index: 37 scientists 122–123 D-Index: 29 scientists 124–125 D-Index: 28 scientists 126–127 D-Index: 24 scientists 128–129 D-Index: 33 scientists 130–131 D-Index: 28 scientists 132–133 D-Index: 21 scientists 134–135 D-Index: 20 scientists 136–137 D-Index: 23 scientists 138–139 D-Index: 17 scientists 140–141 D-Index: 12 scientists 142–143 D-Index: 17 scientists 144–145 D-Index: 21 scientists 146–147 D-Index: 13 scientists 148–149 D-Index: 11 scientists 150–151 D-Index: 14 scientists 152–153 D-Index: 13 scientists 154–155 D-Index: 9 scientists 156–157 D-Index: 10 scientists 158–159 D-Index: 7 scientists 160–161 D-Index: 4 scientists 162–163 D-Index: 4 scientists 164 D-Index: 3 scientists 165+ D-Index: 98 scientists
40 D-Index 165+

This scientist: 42 D-Index — 3rd percentile

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

The last bar groups every scientist with 165 D-Index or more.

Overview

Michael A. Guillorn is affiliated with IBM in the United States. Their research spans several fields related to engineering and computer science, with a focus on electrical and electronic engineering as well as hardware and architecture.

Their main fields of study include:

  • Engineering
  • Computer Science

Subfields of study emphasize:

  • Electrical and Electronic Engineering
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition

Michael A. Guillorn's research covers a range of established topics:

  • Ferroelectric and Negative Capacitance Devices
  • Parallel Computing and Optimization Techniques
  • Advanced Memory and Neural Computing
  • Advanced Neural Network Applications
  • Low-power high-performance VLSI design
  • Advancements in Semiconductor Devices and Circuit Design
  • VLSI and Analog Circuit Testing

The scientist has published papers in notable venues, with frequent publications in:

  • IEEE Journal of Solid-State Circuits
  • Proceedings of the IEEE

Recent publications include:

  • "Efficient AI System Design With Cross-Layer Approximate Computing", 2020, Proceedings of the IEEE
  • "A 7-nm Four-Core Mixed-Precision AI Chip With 26.2-TFLOPS Hybrid-FP8 Training, 104.9-TOPS INT4 Inference, and Workload-Aware Throttling", 2021, IEEE Journal of Solid-State Circuits
  • "Power-Limited Inference Performance Optimization Using a Software-Assisted Peak Current Regulation Scheme in a 5-nm AI SoC", 2024, IEEE Journal of Solid-State Circuits

Michael A. Guillorn has collaborated frequently with several co-authors throughout their career. These include:

  • Swagath Venkataramani
  • Nianzheng Cao
  • Bruce Fleischer
  • Marcel Schaal
  • J. A. Silberman

Best Publications

  • Vertically Aligned Carbon Nanofibers and Related Structures: Controlled Synthesis and Directed Assembly

    Anatoli Vasilievich Melechko;Vladimir I Merkulov;Timothy E McKnight;M. A. Guillorn

  • High performance and highly uniform gate-all-around silicon nanowire MOSFETs with wire size dependent scaling

    S. Bangsaruntip;G. M. Cohen;A. Majumdar;Y. Zhang

  • Alignment mechanism of carbon nanofibers produced by plasma-enhanced chemical-vapor deposition

    Vladimir I. Merkulov;Anatoli V. Melechko;Michael A. Guillorn;Douglas H. Lowndes

  • Shaping carbon nanostructures by controlling the synthesis process

    Vladimir I. Merkulov;Michael A. Guillorn;Douglas H. Lowndes;Michael L. Simpson

  • Intracellular integration of synthetic nanostructures with viable cells for controlled biochemical manipulation

    Timothy E McKnight;Anatoli V Melechko;Guy D Griffin;Michael A Guillorn

  • Gate-all-around silicon nanowire 25-stage CMOS ring oscillators with diameter down to 3 nm

    S. Bangsaruntip;A. Majumdar;G. M. Cohen;S. U. Engelmann

  • Sharp Reduction of Contact Resistivities by Effective Schottky Barrier Lowering With Silicides as Diffusion Sources

    Zhen Zhang;F Pagette;C D'Emic;B Yang

  • Challenges and solutions of FinFET integration in an SRAM cell and a logic circuit for 22 nm node and beyond

    H. Kawasaki;V. S. Basker;T. Yamashita;C.-H. Lin

  • Controlled alignment of carbon nanofibers in a large-scale synthesis process

    Vladimir I. Merkulov;A. V. Melechko;M. A. Guillorn;M. L. Simpson

  • Two-Dimensional Pattern Formation Using Graphoepitaxy of PS-b-PMMA Block Copolymers for Advanced FinFET Device and Circuit Fabrication

    Hsinyu Tsai;Jed W. Pitera;Hiroyuki Miyazoe;Sarunya Bangsaruntip

  • Individually addressable vertically aligned carbon nanofiber-based electrochemical probes

    M. A. Guillorn;T. E. McKnight;A. Melechko;V. I. Merkulov

  • High- $\kappa$ /Metal-Gate Fully Depleted SOI CMOS With Single-Silicide Schottky Source/Drain With Sub-30-nm Gate Length

    M.H. Khater;Zhen Zhang;Jin Cai;C. Lavoie

  • Performance trade-offs in FinFET and gate-all-around device architectures for 7nm-node and beyond

    Seong-Dong Kim;Michael Guillorn;Isaac Lauer;Phil Oldiges

  • A Scalable Multi- TeraOPS Deep Learning Processor Core for AI Trainina and Inference

    Bruce Fleischer;Sunil Shukla;Matthew Ziegler;Joel Silberman

  • Operation of a gated field emitter using an individual carbon nanofiber cathode

    M. A. Guillorn;A. V. Melechko;V. I. Merkulov;E. D. Ellis

  • FinFET performance advantage at 22nm: An AC perspective

    M. Guillorn;J. Chang;A. Bryant;N. Fuller

  • Large-scale synthesis of arrays of high-aspect-ratio rigid vertically aligned carbon nanofibres

    A V Melechko;A V Melechko;T E McKnight;D K Hensley;M A Guillorn;M A Guillorn

  • Density scaling with gate-all-around silicon nanowire MOSFETs for the 10 nm node and beyond

    S. Bangsaruntip;K. Balakrishnan;S.-L Cheng;J. Chang

  • Four-probe charge transport measurements on individual vertically aligned carbon nanofibers

    Lan Zhang;Derek Austin;Vladimir I. Merkulov;Anatoli V. Meleshko

  • Field emission from isolated individual vertically aligned carbon nanocones

    L. R. Baylor;V. I. Merkulov;E. D. Ellis;M. A. Guillorn

Frequent Co-Authors

Josephine B. Chang
Josephine B. Chang Northrop Grumman (United States)
Jeffrey W. Sleight
Jeffrey W. Sleight IBM (United States)
Michael L. Simpson
Michael L. Simpson University of Tennessee at Knoxville
Joy Cheng
Joy Cheng IBM (United States)
Wilfried Haensch
Wilfried Haensch Argonne National Laboratory
Leland Chang
Leland Chang IBM Research - Thomas J. Watson Research Center
Matthew E. Colburn
Matthew E. Colburn Facebook (United States)
Guy M. Cohen
Guy M. Cohen IBM (United States)
Douglas H. Lowndes
Douglas H. Lowndes Oak Ridge National Laboratory
Swagath Venkataramani
Swagath Venkataramani IBM (United States)

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