World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
33
Citations
5693
World Ranking
12528
National Ranking
5086

Reetuparna Das 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 Reetuparna Das 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: 98 publications — 8th percentile

8% of scientists in this discipline score the same or lower.

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

Reetuparna Das 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 Reetuparna Das 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: 33 D-Index — 13th percentile

13% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2019 - Fellow of Alfred P. Sloan Foundation

Overview

Reetuparna Das is affiliated with the University of Michigan-Ann Arbor in the United States. Their research spans multiple disciplines including biochemistry, genetics, molecular biology, and computer science, with notable contributions to molecular biology and artificial intelligence.

Their recent publications cover a range of topics in genomic sequencing, embedded computing, and machine learning applications in bioinformatics. Selected papers include:

  • Rapid Real-time Squiggle Classification for Read until using RawMap, 2023, Archives of Clinical and Biomedical Research
  • Rapid Real-time Squiggle Classification for Read Until Using RawMap, 2022, bioRxiv (Cold Spring Harbor Laboratory)
  • BitSET: Bit-Serial Early Termination for Computation Reduction in Convolutional Neural Networks, 2023, ACM Transactions on Embedded Computing Systems
  • A High-Throughput Pruning-Based Pair-Hidden-Markov-Model Hardware Accelerator for Next-Generation DNA Sequencing, 2020, IEEE Solid-State Circuits Letters
  • Hardware-friendly User-specific Machine Learning for Edge Devices, 2022, ACM Transactions on Embedded Computing Systems

The scientist's work is frequently published in venues such as bioRxiv (Cold Spring Harbor Laboratory), arXiv (Cornell University), Zenodo (CERN European Organization for Nuclear Research), ACM Transactions on Embedded Computing Systems, and Archives of Clinical and Biomedical Research.

Main areas of study include:

  • Biochemistry, Genetics and Molecular Biology
  • Computer Science

Subfields of focus are:

  • Molecular Biology
  • Artificial Intelligence
  • Electrical and Electronic Engineering
  • Computer Networks and Communications
  • Hardware and Architecture

Research topics extensively covered encompass:

  • Genomics and Phylogenetic Studies
  • Advanced Memory and Neural Computing
  • Algorithms and Data Compression
  • Ferroelectric and Negative Capacitance Devices
  • Parallel Computing and Optimization Techniques
  • Machine Learning in Bioinformatics
  • Advanced Neural Network Applications

Reetuparna Das has collaborated frequently with a number of co-authors including Arun Subramaniyan, Satish Narayanasamy, Daichi Fujiki, David Blaauw, and Xiaowei Wang.

Among their contributions to academic literature, they have authored a book titled In-/Near-Memory Computing published in 2021 by Morgan & Claypool Publishers.

Recognition of their professional achievements includes being named a Fellow of the Alfred P. Sloan Foundation in 2019.

Best Publications

  • Neural cache: bit-serial in-cache acceleration of deep neural networks

    Charles Eckert;Xiaowei Wang;Jingcheng Wang;Arun Subramaniyan

  • A novel dimensionally-decomposed router for on-chip communication in 3D architectures

    Jongman Kim;Chrysostomos Nicopoulos;Dongkook Park;Reetuparna Das

  • Scalpel: Customizing DNN Pruning to the Underlying Hardware Parallelism

    Jiecao Yu;Andrew Lukefahr;David Palframan;Ganesh Dasika

  • Compute Caches

    Shaizeen Aga;Supreet Jeloka;Arun Subramaniyan;Satish Narayanasamy

  • MIRA: A Multi-layered On-Chip Interconnect Router Architecture

    Dongkook Park;Soumya Eachempati;Reetuparna Das;Asit K. Mishra

  • Application-aware prioritization mechanisms for on-chip networks

    Reetuparna Das;Onur Mutlu;Thomas Moscibroda;Chita R. Das

  • Design and evaluation of a hierarchical on-chip interconnect for next-generation CMPs

    Reetuparna Das;Soumya Eachempati;Asit K. Mishra;Vijaykrishnan Narayanan

  • Aérgia: exploiting packet latency slack in on-chip networks

    Reetuparna Das;Onur Mutlu;Thomas Moscibroda;Chita R. Das

  • Composite Cores: Pushing Heterogeneity Into a Core

    Andrew Lukefahr;Shruti Padmanabha;Reetuparna Das;Faissal M. Sleiman

  • A 28-nm Compute SRAM With Bit-Serial Logic/Arithmetic Operations for Programmable In-Memory Vector Computing

    Jingcheng Wang;Xiaowei Wang;Charles Eckert;Arun Subramaniyan

  • Catnap: energy proportional multiple network-on-chip

    Reetuparna Das;Satish Narayanasamy;Sudhir K. Satpathy;Ronald G. Dreslinski

  • ANVIL: Software-Based Protection Against Next-Generation Rowhammer Attacks

    Zelalem Birhanu Aweke;Salessawi Ferede Yitbarek;Rui Qiao;Reetuparna Das

  • A case for dynamic frequency tuning in on-chip networks

    Asit K. Mishra;Reetuparna Das;Soumya Eachempati;Ravi Iyer

  • Application-to-core mapping policies to reduce memory system interference in multi-core systems

    R. Das;R. Ausavarungnirun;O. Mutlu;A. Kumar

  • Performance and power optimization through data compression in Network-on-Chip architectures

    R. Das;A.K. Mishra;C. Nicopoulos;Dongkook Park

  • 14.2 A Compute SRAM with Bit-Serial Integer/Floating-Point Operations for Programmable In-Memory Vector Acceleration

    Jingcheng Wang;Xiaowei Wang;Charles Eckert;Arun Subramaniyan

  • In-Memory Data Parallel Processor

    Daichi Fujiki;Scott Mahlke;Reetuparna Das

  • Scalpel

    Unknown

  • Power-Aware NoCs through Routing and Topology Reconfiguration

    Ritesh Parikh;Reetuparna Das;Valeria Bertacco

  • Swizzle-Switch Networks for Many-Core Systems

    K. Sewell;R. G. Dreslinski;T. Manville;S. Satpathy

  • Neural Cache: Bit-Serial In-Cache Acceleration of Deep Neural Networks

    Charles Eckert;Xiaowei Wang;Jingcheng Wang;Arun Subramaniyan

Frequent Co-Authors

David Blaauw
David Blaauw University of Michigan–Ann Arbor
Satish Narayanasamy
Satish Narayanasamy University of Michigan–Ann Arbor
Scott Mahlke
Scott Mahlke University of Michigan–Ann Arbor
Ronald G. Dreslinski
Ronald G. Dreslinski University of Michigan–Ann Arbor
Chita R. Das
Chita R. Das Pennsylvania State University
Trevor Mudge
Trevor Mudge University of Michigan–Ann Arbor
Dennis Sylvester
Dennis Sylvester University of Michigan–Ann Arbor
Onur Mutlu
Onur Mutlu ETH Zurich
Ravi Iyer
Ravi Iyer Intel (United States)
Asit K. Mishra
Asit K. Mishra University College Cork

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