World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
6084
World Ranking
10724
National Ranking
4480

Mattan Erez 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 Mattan Erez 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: 123 publications — 16th percentile

16% of scientists in this discipline score the same or lower.

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

Mattan Erez 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 Mattan Erez 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: 37 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

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

Overview

Mattan Erez is affiliated with The University of Texas at Austin in the United States. Their research primarily focuses on computer science, with specific contributions to artificial intelligence, hardware and architecture, information systems, computer networks and communications, and computer vision and pattern recognition.

Their work spans several key topics within computer science, including parallel computing and optimization techniques, advanced data storage technologies, cloud computing and resource management, stochastic gradient optimization techniques, advanced neural network applications, ferroelectric and negative capacitance devices, and computational physics and Python applications.

Frequent co-authors with whom Mattan Erez has collaborated are Benjamin Y. Cho, Jeageun Jung, Majid Jalili, Michael Orshansky, and Sangkug Lym.

The publication venues where Mattan Erez's research appears most often include:

  • arXiv (Cornell University)
  • IEEE Computer Architecture Letters
  • International Journal of Parallel Programming
  • 2021 36th IEEE/ACM International Conference on Automated Software Engineering (ASE)
  • Zenodo (CERN European Organization for Nuclear Research)

Notable recent papers authored or co-authored by Mattan Erez are:

  • Accelerating bandwidth-bound deep learning inference with main-memory accelerators, 2021, arXiv (Cornell University)
  • FlexSA: Flexible Systolic Array Architecture for Efficient Pruned DNN Model Training, 2020, arXiv (Cornell University)
  • Managing Prefetchers With Deep Reinforcement Learning, 2022, IEEE Computer Architecture Letters
  • Accelerating Bandwidth-Bound Deep Learning Inference with Main-Memory Accelerators, 2020, arXiv (Cornell University)
  • FlexSA: Flexible Systolic Array Architecture for Efficient Pruned DNN Model Training, 2020, arXiv (Cornell University)

Best Publications

  • Sequoia: programming the memory hierarchy

    Kayvon Fatahalian;Daniel Reiter Horn;Timothy J. Knight;Larkhoon Leem

  • Addressing failures in exascale computing

    Marc Snir;Robert W Wisniewski;Jacob A Abraham;Sarita V Adve

  • Merrimac: Supercomputing with Streams

    William J. Dally;Francois Labonte;Abhishek Das;Patrick Hanrahan

  • FREE-p: Protecting non-volatile memory against both hard and soft errors

    Doe Hyun Yoon;Naveen Muralimanohar;Jichuan Chang;Parthasarathy Ranganathan

  • Speculation techniques for improving load related instruction scheduling

    Adi Yoaz;Mattan Erez;Ronny Ronen;Stephan Jourdan

  • Balancing DRAM locality and parallelism in shared memory CMP systems

    Min Kyu Jeong;Doe Hyun Yoon;Dam Sunwoo;Mike Sullivan

  • Virtualized and flexible ECC for main memory

    Doe Hyun Yoon;Mattan Erez

  • A QoS-aware memory controller for dynamically balancing GPU and CPU bandwidth use in an MPSoC

    Min Kyu Jeong;Mattan Erez;Chander Sudanthi;Nigel Paver

  • Memory mapped ECC: low-cost error protection for last level caches

    Doe Hyun Yoon;Mattan Erez

  • A locality-aware memory hierarchy for energy-efficient GPU architectures

    Minsoo Rhu;Michael Sullivan;Jingwen Leng;Mattan Erez

  • Dirigent: Enforcing QoS for Latency-Critical Tasks on Shared Multicore Systems

    Haishan Zhu;Mattan Erez

  • NBTI-aware DVFS: a new approach to saving energy and increasing processor lifetime

    Mehmet Basoglu;Michael Orshansky;Mattan Erez

  • Adaptive granularity memory systems: a tradeoff between storage efficiency and throughput

    Doe Hyun Yoon;Min Kyu Jeong;Mattan Erez

  • Compilation for explicitly managed memory hierarchies

    Timothy J. Knight;Ji Young Park;Manman Ren;Mike Houston

  • Bamboo ECC: Strong, safe, and flexible codes for reliable computer memory

    Jungrae Kim;Michael Sullivan;Mattan Erez

  • Containment domains: a scalable, efficient, and flexible resilience scheme for exascale systems

    Jinsuk Chung;Ikhwan Lee;Michael Sullivan;Jee Ho Ryoo

  • Priority-based cache allocation in throughput processors

    Dong Li;Minsoo Rhu;Daniel R. Johnson;Mike O'Connor

  • NoC with Near-Ideal Express Virtual Channels Using Global-Line Communication

    T. Krishna;A. Kumar;P. Chiang;M. Erez

  • PruneTrain: fast neural network training by dynamic sparse model reconfiguration

    Sangkug Lym;Esha Choukse;Siavash Zangeneh;Wei Wen

  • The dynamic granularity memory system

    Doe Hyun Yoon;Min Kyu Jeong;Michael Sullivan;Mattan Erez

  • Bit-plane compression: transforming data for better compression in many-core architectures

    Jungrae Kim;Michael Sullivan;Esha Choukse;Mattan Erez

Frequent Co-Authors

William J. Dally
William J. Dally Nvidia (United Kingdom)
Jung Ho Ahn
Jung Ho Ahn Seoul National University
Michael Orshansky
Michael Orshansky The University of Texas at Austin
Stephen W. Keckler
Stephen W. Keckler Nvidia (United States)
Pat Hanrahan
Pat Hanrahan Stanford University
Alex Aiken
Alex Aiken Stanford University
Parthasarathy Ranganathan
Parthasarathy Ranganathan Google (United States)
Li-Shiuan Peh
Li-Shiuan Peh National University of Singapore
Avinoam Kolodny
Avinoam Kolodny Technion – Israel Institute of Technology
Ran Ginosar
Ran Ginosar Technion – Israel Institute of Technology

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