World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
30
Citations
4230
World Ranking
14043
National Ranking
5574

Gang Quan 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 Gang Quan 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: 156 publications — 29th percentile

29% of scientists in this discipline score the same or lower.

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

Gang Quan 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 Gang Quan 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: 30 D-Index — 3rd percentile

3% of scientists in this discipline score the same or lower.

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

Overview

Gang Quan is affiliated with Florida International University in the United States. Their research focuses primarily on computer science, with a notable emphasis on artificial intelligence, materials chemistry, electrical and electronic engineering, computer networks and communications, and hardware and architecture.

The scientist's work covers several topics, including:

  • Cryptography and Data Security
  • Coding theory and cryptography
  • Thermal properties of materials
  • Advanced Thermoelectric Materials and Devices
  • Chaos-based Image/Signal Encryption
  • Complexity and Algorithms in Graphs
  • Advanced Data Storage Technologies

Gang Quan has published in a range of venues, reflecting an interdisciplinary approach. The frequent publication venues include:

  • arXiv (Cornell University)
  • Materials Today Physics
  • The Journal of Supercomputing
  • 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE)
  • ACM Transactions on Design Automation of Electronic Systems

Recent notable papers authored or co-authored by Gang Quan are:

  • CryptoGCN: Fast and Scalable Homomorphically Encrypted Graph Convolutional Network Inference, 2022, arXiv (Cornell University)
  • On Fundamental Principles for Thermal-Aware Design on Periodic Real-Time Multi-Core Systems, 2020, ACM Transactions on Design Automation of Electronic Systems
  • Secure and efficient general matrix multiplication on cloud using homomorphic encryption, 2024, The Journal of Supercomputing
  • Do Temperature and Humidity Exposures Hurt or Benefit Your SSDs?, 2022, 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE)
  • Thermal Aware System-Wide Reliability Optimization for Automotive Distributed Computing Applications, 2022, IEEE Transactions on Vehicular Technology

The scientist has collaborated frequently with several co-authors, including:

  • Wujie Wen
  • Liqiang Wang
  • Te-Huan Liu
  • Ronggui Yang
  • Soamar Homsi

Best Publications

  • Online optimization for scheduling preemptable tasks on IaaS cloud systems

    Jiayin Li;Meikang Qiu;Zhong Ming;Gang Quan

  • Energy efficient fixed-priority scheduling for real-time systems on variable voltage processors

    Gang Quan;Xiaobo Hu

  • Enhanced fixed-priority scheduling with (m,k)-firm guarantee

    Gang Quan;Xiaobo Hu

  • Throughput maximization for periodic real-time systems under the maximal temperature constraint

    Huang Huang;Vivek Chaturvedi;Gang Quan;Jeffrey Fan

  • Resource allocation robustness in multi-core embedded systems with inaccurate information

    Jiayin Li;Zhong Ming;Meikang Qiu;Gang Quan

  • Reducing both dynamic and leakage energy consumption for hard real-time systems

    Linwei Niu;Gang Quan

  • Searching for multiobjective preventive maintenance schedules: Combining preferences with evolutionary algorithms

    Gang Quan;Garrison W. Greenwood;Donglin Liu;Sharon Hu

  • On-Line Scheduling of Real-Time Services for Cloud Computing

    Shuo Liu;Gang Quan;Shangping Ren

  • Minimal energy fixed-priority scheduling for variable voltage processors

    Gang Quan;Xiaobo Sharon Hu

  • Data Allocation for Hybrid Memory With Genetic Algorithm

    Meikang Qiu;Zhi Chen;Jianwei Niu;Ziliang Zong

  • DeepN-JPEG: a deep neural network favorable JPEG-based image compression framework

    Zihao Liu;Tao Liu;Wujie Wen;Lei Jiang

  • Informer homed routing fault tolerance mechanism for wireless sensor networks

    Meikang Qiu;Zhong Ming;Jiayin Li;Jianning Liu

  • Minimum energy fixed-priority scheduling for variable voltage processors

    Gang Quan;X.S. Hu

  • A realistic variable voltage scheduling model for real-time applications

    Bren Mochocki;Xiaobo Sharon Hu;Gang Quan

  • Feasibility Analysis for Temperature-Constraint Hard Real-Time Periodic Tasks

    Gang Quan;V Chaturvedi

  • Energy minimization for real-time systems with (m,k)-guarantee

    Linwei Niu;Gang Quan

  • Fixed priority scheduling for reducing overall energy on variable voltage processors

    Gang Quan;Linwei Niu;X.S. Hu;B. Mochocki

  • A unified approach to variable voltage scheduling for nonideal DVS processors

    B.C. Mochocki;X.S. Hu;Gang Quan

  • Neighbor-aware dynamic thermal management for multi-core platform

    Guanglei Liu;Ming Fan;Gang Quan

  • Leakage Aware Feasibility Analysis for Temperature-Constrained Hard Real-Time Periodic Tasks

    Gang Quan;Yan Zhang

  • Energy efficient DVS schedule for fixed-priority real-time systems

    Gang Quan;Xiaobo Sharon Hu

  • Throughput maximization for periodic real-time systems under the maximal temperature constraint

    Huang Huang;Gang Quan;Jeffrey Fan;Meikang Qiu

Frequent Co-Authors

Shaolei Ren
Shaolei Ren University of California, Riverside
Meikang Qiu
Meikang Qiu Augusta University
Xiaobo Sharon Hu
Xiaobo Sharon Hu University of Notre Dame
Lei Jiang
Lei Jiang Chinese Academy of Sciences
Yier Jin
Yier Jin University of Florida
Xiao Qin
Xiao Qin Auburn University
Yanzhi Wang
Yanzhi Wang Northeastern University
Nguyen H. Tran
Nguyen H. Tran University of Sydney
Laurence T. Yang
Laurence T. Yang St. Francis Xavier University
Antonello Monti
Antonello Monti RWTH Aachen University

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