World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
35
Citations
5397
World Ranking
11680
National Ranking
353

Xiao Liu 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 Xiao Liu 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: 183 publications — 40th percentile

40% of scientists in this discipline score the same or lower.

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

Xiao Liu 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 Xiao Liu 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: 35 D-Index — 20th percentile

20% of scientists in this discipline score the same or lower.

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

Overview

Xiao Liu is affiliated with Deakin University in Australia and has a research portfolio primarily focused on computer science and engineering. Their work spans a wide range of specialized subfields including artificial intelligence, computer vision and pattern recognition, information systems, computer networks and communications, and aerospace engineering.

They have contributed to topics such as topic modeling, IoT and edge/fog computing, natural language processing techniques, software engineering research, cloud computing and resource management, advanced neural network applications, and privacy-preserving technologies in data.

The recent publications of Xiao Liu demonstrate involvement in both foundational and applied research. Notable papers include:

  • Dynamic Prefix-Tuning for Generative Template-based Event Extraction (2022), published in the Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

While other prominent papers credited to authors with similar names appear in various fields, the paper listed above specifically attributes to Xiao Liu.

Xiao Liu frequently collaborates with other researchers, with recurrent coauthors including:

  • Xuejun Li (25 joint works)
  • Xu Jia (16 joint works)
  • Frank Jiang (13 joint works)
  • Jin Liu (9 joint works)
  • Aiting Yao (8 joint works)

Their work is regularly published in several venues, such as:

  • arXiv (Cornell University) with 46 publications
  • SSRN Electronic Journal with 14 publications
  • Journal of Systems and Software with 6 publications
  • Concurrency and Computation Practice and Experience with 5 publications
  • Information Processing & Management with 4 publications

The volume of research across computer science and engineering fields indicates a broad scope encompassing theoretical exploration and practical applications. Their expertise includes the development and application of natural language processing techniques and advanced neural networks, alongside a focus on data privacy and resource management within cloud and distributed systems.

Best Publications

  • A data placement strategy in scientific cloud workflows

    Dong Yuan;Yun Yang;Xiao Liu;Jinjun Chen

  • A market-oriented hierarchical scheduling strategy in cloud workflow systems

    Zhangjun Wu;Zhangjun Wu;Xiao Liu;Zhiwei Ni;Dong Yuan

  • An empirical study of product differences in consumers’ E-commerce adoption behavior

    Xiao Liu;Kwok Kee Wei

  • A Revised Discrete Particle Swarm Optimization for Cloud Workflow Scheduling

    Zhangjun Wu;Zhiwei Ni;Lichuan Gu;Xiao Liu

  • A Compromised-Time-Cost Scheduling Algorithm in SwinDeW-C for Instance-Intensive Cost-Constrained Workflows on a Cloud Computing Platform

    Ke Liu;Hai Jin;Jinjun Chen;Xiao Liu

  • A structured analysis of unstructured big data by leveraging cloud computing

    Xiao Liu;Param Vir Singh;Kannan Srinivasan

  • A survey on multimodal data-driven smart healthcare systems: approaches and applications

    Qiong Cai;Hao Wang;Zhenmin Li;Xiao Liu

  • On-demand minimum cost benchmarking for intermediate dataset storage in scientific cloud workflow systems

    Dong Yuan;Yun Yang;Xiao Liu;Jinjun Chen

  • A cost-effective strategy for intermediate data storage in scientific cloud workflow systems

    Dong Yuan;Yun Yang;Xiao Liu;Jinjun Chen

  • A Highly Practical Approach toward Achieving Minimum Data Sets Storage Cost in the Cloud

    Dong Yuan;Yun Yang;Xiao Liu;Wenhao Li

  • The Design of Cloud Workflow Systems

    Xiao Liu;Dong Yuan;Gaofeng Zhang;Wenhao Li

  • An Algorithm in SwinDeW-C for Scheduling Transaction-Intensive Cost-Constrained Cloud Workflows

    Yun Yang;Ke Liu;Jinjun Chen;Xiao Liu

  • A data dependency based strategy for intermediate data storage in scientific cloud workflow systems

    Dong Yuan;Yun Yang;Xiao Liu;Gaofeng Zhang

  • Preventing Temporal Violations in Scientific Workflows: Where and How

    Xiao Liu;Yun Yang;Yuanchun Jiang;Jinjun Chen

  • A novel statistical time-series pattern based interval forecasting strategy for activity durations in workflow systems

    Xiao Liu;Zhiwei Ni;Dong Yuan;Yuanchun Jiang

  • SwinDeW-C: A Peer-to-Peer Based Cloud Workflow System

    Xiao Liu;Dong Yuan;Gaofeng Zhang;Jinjun Chen

  • Do we need to handle every temporal violation in scientific workflow systems

    Xiao Liu;Yun Yang;Dong Yuan;Jinjun Chen

  • A Generic QoS Framework for Cloud Workflow Systems

    Xiao Liu;Yun Yang;Dong Yuan;Gaofeng Zhang

  • SynCoBERT: Syntax-Guided Multi-Modal Contrastive Pre-Training for Code Representation

    Xin Wang;Yasheng Wang;Fei Mi;Pingyi Zhou

  • CSMC: A combination strategy for multi-class classification based on multiple association rules

    Ye-Zheng Liu;Yuan-Chun Jiang;Xiao Liu;Shan-Lin Yang

  • FogWorkflowSim: an automated simulation toolkit for workflow performance evaluation in fog computing

    Xiao Liu;Lingmin Fan;Jia Xu;Xuejun Li

  • EXPRESS: an energy-efficient and secure framework for mobile edge computing and blockchain based smart systems

    Jia Xu;Xiao Liu;Xuejun Li;Lei Zhang

Frequent Co-Authors

Yun Yang
Yun Yang Swinburne University of Technology
Jinjun Chen
Jinjun Chen Swinburne University of Technology
Xi Zheng
Xi Zheng Macquarie University
Qiang He
Qiang He Swinburne University of Technology
Shiliang Sun
Shiliang Sun East China Normal University
John Grundy
John Grundy Monash University
Cheng Wang
Cheng Wang Xiamen University
Zijiang Yang
Zijiang Yang Western Michigan University
Jonathan Li
Jonathan Li University of Waterloo
Jianping Fan
Jianping Fan University of North Carolina at Charlotte

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