World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
7754
World Ranking
9644
National Ranking
4086

Rakesh Kumar 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 Rakesh Kumar 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: 150 publications — 27th percentile

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

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

Rakesh Kumar 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 Rakesh Kumar 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: 39 D-Index — 33rd percentile

33% of scientists in this discipline score the same or lower.

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

Overview

Rakesh Kumar is affiliated with the University of Illinois at Urbana-Champaign in the United States. Their research primarily focuses on several aspects of computer science, particularly within hardware and architecture, computer networks and communications, and information systems. They have also contributed to the fields of electrical and electronic engineering and artificial intelligence.

Their main fields of study involve the broader area of computer science with a specific emphasis on subfields such as:

  • Hardware and Architecture
  • Computer Networks and Communications
  • Information Systems
  • Electrical and Electronic Engineering
  • Artificial Intelligence

Within these areas, the key topics that frequently appear in their work include:

  • Parallel Computing and Optimization Techniques
  • Embedded Systems Design Techniques
  • Interconnection Networks and Systems
  • Cloud Computing and Resource Management
  • IoT and Edge/Fog Computing
  • AI in cancer detection
  • Artificial Intelligence in Healthcare

Rakesh Kumar's recent publications cover a range of topics related to embedded platforms, thermal management, network-on-chip architectures, and machine learning applications. Some noteworthy papers include:

  • "Design Space Exploration for Chiplet-Assembly-Based Processors" (2020) published in IEEE Transactions on Very Large Scale Integration (VLSI) Systems
  • "A Novel Multi-Neural Ensemble Approach for Cancer Diagnosis" (2021) published in Applied Artificial Intelligence
  • "Application driven routing for mesh based Network-on-Chip architectures" (2022) published in Integration
  • "Application Phase Behavior-Guided Thermal Management of Embedded Platforms" (2020) published in IEEE Embedded Systems Letters
  • "Machine learning guided thermal management of Open Computing Language applications on CPU-GPU based embedded platforms" (2022) published in IET Computers & Digital Techniques

The scholar has collaborated with various co-authors throughout their career. Frequent collaborators include:

  • Bibhas Ghoshal
  • Akash Sachan
  • Ankur Gogoi
  • Saptadeep Pal
  • Daniel Petrisko

Publication venues where Rakesh Kumar has contributed multiple works reflect the interdisciplinary nature of their research. These venues include:

  • IEEE Transactions on Very Large Scale Integration (VLSI) Systems
  • Applied Artificial Intelligence
  • Integration
  • IEEE Embedded Systems Letters
  • IET Computers & Digital Techniques

Best Publications

  • Single-ISA heterogeneous multi-core architectures: the potential for processor power reduction

    Rakesh Kumar;Keith I. Farkas;Norman P. Jouppi;Parthasarathy Ranganathan

  • Single-ISA Heterogeneous Multi-Core Architectures for Multithreaded Workload Performance

    Rakesh Kumar;Dean M. Tullsen;Parthasarathy Ranganathan;Norman P. Jouppi

  • Interconnections in Multi-Core Architectures: Understanding Mechanisms, Overheads and Scaling

    Rakesh Kumar;Victor Zyuban;Dean M. Tullsen

  • Heterogeneous chip multiprocessors

    R. Kumar;D.M. Tullsen;N.P. Jouppi;P. Ranganathan

  • Core architecture optimization for heterogeneous chip multiprocessors

    Rakesh Kumar;Dean M. Tullsen;Norman P. Jouppi

  • On reconfiguration-oriented approximate adder design and its application

    Rong Ye;Ting Wang;Feng Yuan;Rakesh Kumar

  • Slack redistribution for graceful degradation under voltage overscaling

    Andrew B. Kahng;Seokhyeong Kang;Rakesh Kumar;John Sartori

  • Stochastic computation

    Naresh R. Shanbhag;Rami A. Abdallah;Rakesh Kumar;Douglas L. Jones

  • Scalable stochastic processors

    Sriram Narayanan;John Sartori;Rakesh Kumar;Douglas L. Jones

  • Underdesigned and Opportunistic Computing in Presence of Hardware Variability

    P. Gupta;Y. Agarwal;L. Dolecek;N. Dutt

  • Designing a processor from the ground up to allow voltage/reliability tradeoffs

    Andrew B. Kahng;Seokhyeong Kang;Rakesh Kumar;John Sartori

  • Algorithmic approaches to low overhead fault detection for sparse linear algebra

    Joseph Sloan;Rakesh Kumar;Greg Bronevetsky

  • Conjoined-Core Chip Multiprocessing

    Rakesh Kumar;Norman P. Jouppi;Dean M. Tullsen

  • Branch and Data Herding: Reducing Control and Memory Divergence for Error-Tolerant GPU Applications

    J. Sartori;R. Kumar

  • Exploiting unbalanced thread scheduling for energy and performance on a CMP of SMT processors

    Matthew DeVuyst;Rakesh Kumar;Dean M. Tullsen

  • Processor Power Reduction Via Single-ISA Heterogeneous Multi-Core Architectures

    R. Kumar;K. Farkas;N.P. Jouppi;P. Ranganathan

  • Hardware Acceleration of Graph Neural Networks

    Adam Auten;Matthew Tomei;Rakesh Kumar

  • On the efficacy of NBTI mitigation techniques

    Tuck-Boon Chan;John Sartori;Puneet Gupta;Rakesh Kumar

  • Proximity-aware directory-based coherence for multi-core processor architectures

    Jeffery A. Brown;Rakesh Kumar;Dean Tullsen

  • End-to-End Network Delay Guarantees for Real-Time Systems Using SDN

    Rakesh Kumar;Monowar Hasan;Smruti Padhy;Konstantin Evchenko

Frequent Co-Authors

Supun Samarasekera
Supun Samarasekera SRI International
Dean M. Tullsen
Dean M. Tullsen University of California, San Diego
Harpreet Sawhney
Harpreet Sawhney Microsoft (United States)
Abass Alavi
Abass Alavi University of Pennsylvania
Norman P. Jouppi
Norman P. Jouppi Google (United States)
David M. Nicol
David M. Nicol University of Illinois at Urbana-Champaign
Puneet Gupta
Puneet Gupta University of California, Los Angeles
Andrew B. Kahng
Andrew B. Kahng University of California, San Diego
Parthasarathy Ranganathan
Parthasarathy Ranganathan Google (United States)

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