World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
31
Citations
4997
World Ranking
13529
National Ranking
5403

Andreas Gerstlauer 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 Andreas Gerstlauer 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: 215 publications — 52nd percentile

52% of scientists in this discipline score the same or lower.

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

Andreas Gerstlauer 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 Andreas Gerstlauer 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: 31 D-Index — 6th percentile

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

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

Overview

Andreas Gerstlauer is affiliated with The University of Texas at Austin in the United States. Their research contributions span several areas within computer science and engineering, with a particular emphasis on hardware design, parallel computing, and security.

Their recent publications include:

  • Exploiting Errors for Efficiency, 2020, ACM Computing Surveys
  • DeeperThings: Fully Distributed CNN Inference on Resource-Constrained Edge Devices, 2021, International Journal of Parallel Programming
  • Machine Learning-Based Microarchitecture-Level Power Modeling of CPUs, 2022, IEEE Transactions on Computers
  • Horizontal Side-Channel Vulnerabilities of Post-Quantum Key Exchange and Encapsulation Protocols, 2021, ACM Transactions on Embedded Computing Systems
  • Aging Compensation With Dynamic Computation Approximation, 2020, IEEE Transactions on Circuits and Systems I Regular Papers

Among frequent co-authors collaborating with Gerstlauer are Hussam Amrouch, Michael Orshansky, Jörg Henkel, Erika S. Alcorta, and Pranav Rama.

The scientist regularly publishes in several prominent venues including:

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

Gerstlauer's main fields of study encompass computer science and engineering. Their subfields of focus include:

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

The primary topics addressed in their work are:

  • Parallel Computing and Optimization Techniques
  • Low-power high-performance VLSI design
  • Advanced Memory and Neural Computing
  • Advanced Data Storage Technologies
  • Advanced Neural Network Applications
  • Adversarial Robustness in Machine Learning
  • Cryptographic Implementations and Security

Best Publications

  • DeepThings: Distributed Adaptive Deep Learning Inference on Resource-Constrained IoT Edge Clusters

    Zhuoran Zhao;Kamyar Mirzazad Barijough;Andreas Gerstlauer

  • Embedded System Design: Modeling, Synthesis and Verification

    Daniel D. Gajski;Samar Abdi;Andreas Gerstlauer;Gunar Schirner

  • Electronic System-Level Synthesis Methodologies

    A. Gerstlauer;C. Haubelt;A.D. Pimentel;T.P. Stefanov

  • RTOS Modeling for System Level Design

    Andreas Gerstlauer;Haobo Yu;Daniel D. Gajski

  • System Design: A Practical Guide with SpecC

    Daniel D. Gajski;Rainer Domer;Junyu Peng;Andreas Gerstlauer

  • Modeling and synthesis of quality-energy optimal approximate adders

    Jin Miao;Ku He;Andreas Gerstlauer;Michael Orshansky

  • System-on-chip environment: a SpecC-based framework for heterogeneous MPSoC design

    Rainer Dömer;Andreas Gerstlauer;Junyu Peng;Dongwan Shin

  • Reliability-aware design to suppress aging

    Hussam Amrouch;Behnam Khaleghi;Andreas Gerstlauer;Jorg Henkel

  • Approximate logic synthesis under general error magnitude and frequency constraints

    Jin Miao;Andreas Gerstlauer;Michael Orshansky

  • Codesign Tradeoffs for High-Performance, Low-Power Linear Algebra Architectures

    A. Pedram;R. A. van de Geijn;A. Gerstlauer

  • Accurate phase-level cross-platform power and performance estimation

    Xinnian Zheng;Lizy K. John;Andreas Gerstlauer

  • Retargetable profiling for rapid, early system-level design space exploration

    Lukai Cai;Andreas Gerstlauer;Daniel Gajski

  • High-level synthesis of approximate hardware under joint precision and voltage scaling

    Seogoo Lee;Lizy K. John;Andreas Gerstlauer

  • System-level abstraction semantics

    Andreas Gerstlauer;Daniel D. Gajski

  • RTOS scheduling in transaction level models

    Haobo Yu;Andreas Gerstlauer;Daniel Gajski

  • Multi-level approximate logic synthesis under general error constraints

    Jin Miao;Andreas Gerstlauer;Michael Orshansky

  • C-based Interactive RTL Design Methodology

    Dongwan Shin;Andreas Gerstlauer;Rainer Dömer;Daniel Gajski

  • The next generation of virtual prototyping: ultra-fast yet accurate simulation of HW/SW systems

    Oliver Bringmann;Wolfgang Ecker;Andreas Gerstlauer;Ajay Goyal

  • DeeperThings: Fully Distributed CNN Inference on Resource-Constrained Edge Devices

    Rafael Stahl;Alexander Hoffman;Daniel Mueller-Gritschneder;Andreas Gerstlauer

  • Abstract, Multifaceted Modeling of Embedded Processors for System Level Design

    G. Schirner;A. Gerstlauer;R. Domer

  • Exploiting Errors for Efficiency: A Survey from Circuits to Applications

    Phillip Stanley-Marbell;Armin Alaghi;Michael Carbin;Eva Darulova

  • Horizontal side-channel vulnerabilities of post-quantum key exchange protocols

    Aydin Aysu;Youssef Tobah;Mohit Tiwari;Andreas Gerstlauer

Frequent Co-Authors

Daniel D. Gajski
Daniel D. Gajski University of California, Irvine
Lizy K. John
Lizy K. John The University of Texas at Austin
Jorg Henkel
Jorg Henkel Karlsruhe Institute of Technology
Michael Orshansky
Michael Orshansky The University of Texas at Austin
Robert A. van de Geijn
Robert A. van de Geijn The University of Texas at Austin
Robert W. Heath
Robert W. Heath University of California, San Diego
Sriram Vishwanath
Sriram Vishwanath The University of Texas at Austin
Jürgen Teich
Jürgen Teich University of Erlangen-Nuremberg
Ulf Schlichtmann
Ulf Schlichtmann Technical University of Munich
George Biros
George Biros The University of Texas at Austin

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