World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
32
Citations
3297
World Ranking
13295
National Ranking
203

Avi Mendelson 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 Avi Mendelson 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: 159 publications — 30th percentile

30% of scientists in this discipline score the same or lower.

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

Avi Mendelson 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 Avi Mendelson 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: 32 D-Index — 10th percentile

10% of scientists in this discipline score the same or lower.

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

Overview

Avi Mendelson is affiliated with the Technion - Israel Institute of Technology in Israel. Their research spans primarily the fields of Computer Science and Engineering, with a total of 58 and 18 publications respectively. Within these main fields, their work is notably concentrated in subfields such as Artificial Intelligence, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Hardware and Architecture, and Civil and Structural Engineering.

The scientist's research topics include a breadth of areas such as Advanced Neural Network Applications, Anomaly Detection Techniques and Applications, Adversarial Robustness in Machine Learning, Domain Adaptation and Few-Shot Learning, Security and Verification in Computing, Semiconductor Materials and Devices, and Physical Unclonable Functions (PUFs) and Hardware Security.

Their publication record features several recent papers that reflect these research interests, including:

  • Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels, 2022, 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
  • A survey of algorithmic methods in IC reverse engineering, 2021, Journal of Cryptographic Engineering
  • NICE: Noise Injection and Clamping Estimation for Neural Network Quantization, 2021, Mathematics
  • Research in computing-intensive simulations for nature-oriented civil-engineering and related scientific fields, using machine learning and big data: an overview of open problems, 2023, Journal Of Big Data
  • Loss aware post-training quantization, 2021, Machine Learning

The venues where Avi Mendelson frequently publishes include arXiv (Cornell University) with 13 papers, Mathematics with 3 papers, Journal Of Big Data with 2 papers, Journal of Low Power Electronics and Applications with 2 papers, and the 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) with 1 paper.

Collaboration is a notable aspect of their research activity. Frequent co-authors include Chaim Baskin, Evgenii Zheltonozhskii, Alex Bronstein, Freddy Gabbay, and Brian Chmiel.

Best Publications

  • Coming challenges in microarchitecture and architecture

    R. Ronen;A. Mendelson;K. Lai;Shih-Lien Lu

  • Pci express prefetching

    Jasmin Ajanovic;Mahesh Wagh;Prashant Sethi;Debendra Das Sharma

  • Many-Core vs. Many-Thread Machines: Stay Away From the Valley

    Z. Guz;E. Bolotin;I. Keidar;A. Kolodny

  • DiDi: Mitigating the Performance Impact of TLB Shootdowns Using a Shared TLB Directory

    Carlos Villavieja;Vasileios Karakostas;Lluis Vilanova;Yoav Etsion

  • Can program profiling support value prediction

    Freddy Gabbay;Avi Mendelson

  • Using value prediction to increase the power of speculative execution hardware

    Freddy Gabbay;Avi Mendelson

  • Shared virtual memory

    Hu Chen;Ying Gao;Xiaocheng Zhou;Shoumeng Yan

  • Programming model for a heterogeneous x86 platform

    Bratin Saha;Xiaocheng Zhou;Hu Chen;Ying Gao

  • The effect of instruction fetch bandwidth on value prediction

    Freddy Gabbay;Avi Mendelson

  • Loss aware post-training quantization

    Yury Nahshan;Brian Chmiel;Brian Chmiel;Chaim Baskin;Evgenii Zheltonozhskii

  • TERAFLUX: Harnessing dataflow in next generation teradevices

    Roberto Giorgi;Rosa M. Badia;François Bodin;Albert Cohen

  • Fairness and Throughput in Switch on Event Multithreading

    Ron Gabor;Shlomo Weiss;Avi Mendelson

  • Micro-operation cache: a power aware frontend for variable instruction length ISA

    B. Solomon;A. Mendelson;R. Ronen;D. Orenstien

  • A survey of algorithmic methods in IC reverse engineering.

    Leonid Azriel;Julian Speith;Nils Albartus;Ran Ginosar

  • On Estimating Optimal Performance of CPU Dynamic Thermal Management

    A. Cohen;F. Finkelstein;A. Mendelson;R. Ronen

  • Designing high-performance and reliable superscalar architectures-the out of order reliable superscalar (O3RS) approach

    A. Mendelson;N. Suri

  • Contrast to Divide: self-supervised pre-training for learning with noisy labels

    Evgenii Zheltonozhskii;Chaim Baskin;Avi Mendelson;Alex M. Bronstein

  • Deep-dive analysis of the data analytics workload in CloudSuite.

    Ahmad Yasin;Yosi Ben-Asher;Avi Mendelson

  • Micro-operation cache: a power aware frontend for the variable instruction length ISA

    Baruch Solomon;Avi Mendelson;Doron Orenstein;Yoav Almog

  • Power Awareness through Selective Dynamically Optimized Traces

    Roni Rosner;Yoav Almog;Micha Moffie;Naftali Schwartz

  • Analysis of Thermal Monitor features of the Intel® Pentium® M Processor

    Efi Rotem;Alon Naveh;Micha Moffie;Avi Mendelson

  • Design Alternatives of Multithreaded Architecture

    Avi Mendelson;Michael Bekerman

  • Power and thermal constraints of modern system-on-a-chip computer

    Efraim Rotem;Ran Ginosar;Avi Mendelson;Uri C. Weiser

Frequent Co-Authors

Alexander M. Bronstein
Alexander M. Bronstein Technion – Israel Institute of Technology
Ran Ginosar
Ran Ginosar Technion – Israel Institute of Technology
Assaf Schuster
Assaf Schuster Technion – Israel Institute of Technology
Raja Giryes
Raja Giryes Tel Aviv University
Avinoam Kolodny
Avinoam Kolodny Technion – Israel Institute of Technology
Bratin Saha
Bratin Saha Amazon (United States)
Paolo Faraboschi
Paolo Faraboschi Hewlett Packard Enterprise (United States)
Christof Paar
Christof Paar Max Planck Institute for Security and Privacy
Dejan Milojicic
Dejan Milojicic Hewlett-Packard (United States)
Albert Cohen
Albert Cohen Google (United States)

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