World's Best Scientists 2026 revealed!
Xuanzhe Liu

Xuanzhe Liu

D-Index & Metrics

Computer Science

D-Index
41
Citations
5736
World Ranking
8956
National Ranking
1153

Xuanzhe 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 Xuanzhe 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: 236 publications — 58th percentile

58% of scientists in this discipline score the same or lower.

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

Xuanzhe 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 Xuanzhe 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: 41 D-Index — 40th percentile

40% 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

  • 2020 - ACM Senior Member

Overview

Xuanzhe Liu is affiliated with Peking University in China and has contributed extensively to the field of computer science, with a primary focus on areas such as computer networks and communications, information systems, and artificial intelligence. The breadth of their research encompasses several subfields including computer vision, pattern recognition, and electrical and electronic engineering.

The scientist's work is notably present in various publication venues, including:

  • arXiv (Cornell University)
  • ACM Transactions on Software Engineering and Methodology
  • IEEE Transactions on Mobile Computing
  • IEEE Transactions on Services Computing
  • Science China Information Sciences

Xuanzhe Liu has collaborated frequently with several co-authors, including Gang Huang, Zhenpeng Chen, Xin Jin, Haoyu Wang, and Mengwei Xu. These collaborations reflect a consistent engagement with peers in the research community over time.

Their research spans a range of topics such as:

  • IoT and Edge/Fog Computing
  • Cloud Computing and Resource Management
  • Advanced Neural Network Applications
  • Software System Performance and Reliability
  • Software Engineering Research
  • Topic Modeling
  • Privacy-Preserving Technologies in Data

Recent papers authored or co-authored by Xuanzhe Liu demonstrate a range of interests and publication outlets. Notable examples include:

  • "Self-Healing Hydrogel Embodied with Macrophage-Regulation and Responsive-Gene-Silencing Properties for Synergistic Prevention of Peritendinous Adhesion," 2021, Advanced Materials
  • "Rise of the Planet of Serverless Computing: A Systematic Review," 2023, ACM Transactions on Software Engineering and Methodology
  • "Enjoy your observability: an industrial survey of microservice tracing and analysis," 2021, Empirical Software Engineering
  • "The Case for FPGA-Based Edge Computing," 2020, IEEE Transactions on Mobile Computing
  • FaaSLight: General Application-level Cold-start Latency Optimization for Function-as-a-Service in Serverless Computing," 2023, ACM Transactions on Software Engineering and Methodology

In addition to articles, Xuanzhe Liu has contributed to book publications, including a work titled "Blockchain and Trustworthy Systems," published by Springer Science+Business Media in 2021.

The scientist was recognized with the ACM Senior Member award in 2020, indicating a level of professional acknowledgement within the computing community.

Best Publications

  • Towards Service Composition Based on Mashup

    Xuanzhe Liu;Yi Hui;Wei Sun;Haiqi Liang

  • Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction

    Ziniu Hu;Weiqing Liu;Jiang Bian;Xuanzhe Liu

  • Learning from the ubiquitous language: an empirical analysis of emoji usage of smartphone users

    Xuan Lu;Wei Ai;Xuanzhe Liu;Qian Li

  • A First Look at Deep Learning Apps on Smartphones

    Mengwei Xu;Jiawei Liu;Yuanqiang Liu;Felix Xiaozhu Lin

  • Refactoring android Java code for on-demand computation offloading

    Ying Zhang;Gang Huang;Xuanzhe Liu;Wei Zhang

  • DeepCache: Principled Cache for Mobile Deep Vision

    Mengwei Xu;Mengze Zhu;Yunxin Liu;Felix Xiaozhu Lin

  • A detailed and real-time performance monitoring framework for blockchain systems

    Peilin Zheng;Zibin Zheng;Xiapu Luo;Xiangping Chen

  • A first look at blockchain-based decentralized applications

    Kaidong Wu;Yun Ma;Gang Huang;Xuanzhe Liu

  • Discovering Homogeneous Web Service Community in the User-Centric Web Environment

    Xuanzhe Liu;Gang Huang;Hong Mei

  • Characterizing Smartphone Usage Patterns from Millions of Android Users

    Huoran Li;Xuan Lu;Xuanzhe Liu;Tao Xie

  • Characterizing Impacts of Heterogeneity in Federated Learning upon Large-Scale Smartphone Data

    Chengxu Yang;Qipeng Wang;Mengwei Xu;Zhenpeng Chen

  • DeepWear: Adaptive Local Offloading for On-Wearable Deep Learning

    Mengwei Xu;Feng Qian;Mengze Zhu;Feifan Huang

  • Rise of the Planet of Serverless Computing: A Systematic Review

    Unknown

  • A comprehensive study on challenges in deploying deep learning based software

    Zhenpeng Chen;Yanbin Cao;Yuanqiang Liu;Haoyu Wang

  • From cloud to edge: a first look at public edge platforms

    Mengwei Xu;Zhe Fu;Xiao Ma;Li Zhang

  • Untangling emoji popularity through semantic embeddings

    Wei Ai;Xuan Lu;Xuanzhe Liu;Ning Wang

  • How Does Web Service API Evolution Affect Clients

    Jun Li;Yingfei Xiong;Xuanzhe Liu;Lu Zhang

  • Melon: breaking the memory wall for resource-efficient on-device machine learning

    Unknown

  • Enjoy your observability: an industrial survey of microservice tracing and analysis

    Bowen Li;Xin Peng;Qilin Xiang;Hanzhang Wang

  • Model-Based Automated Navigation and Composition of Complex Service Mashups

    Gang Huang;Yun Ma;Xuanzhe Liu;Yuchong Luo

  • Multi-resource interleaving for deep learning training

    Unknown

  • Integrating Resource Consumption and Allocation for Infrastructure Resources on-Demand

    Ying Zhang;Gang Huang;Xuanzhe Liu;Hong Mei

  • ShuffleDog: Characterizing and Adapting User-Perceived Latency of Android Apps

    Gang Huang;Mengwei Xu;Felix Xiaozhu Lin;Yunxin Liu

  • iMashup: a mashup-based framework for service composition

    Xuan Zhe Liu;Gang Huang;Qi Zhao;Hong Mei

  • Through a Gender Lens: An Empirical Study of Emoji Usage over Large-Scale Android Users.

    Zhenpeng Chen;Xuan Lu;Sheng Shen;Wei Ai

Frequent Co-Authors

Gang Huang
Gang Huang Peking University
Hong Mei
Hong Mei Peking University
Qiaozhu Mei
Qiaozhu Mei University of Michigan–Ann Arbor
Tao Xie
Tao Xie Peking University
Xiapu Luo
Xiapu Luo Hong Kong Polytechnic University
Feng Qian
Feng Qian University of Southern California
Shangguang Wang
Shangguang Wang Beijing University of Posts and Telecommunications
Kaigui Bian
Kaigui Bian Peking University
Tie-Yan Liu
Tie-Yan Liu Microsoft (United States)
Xuxian Jiang
Xuxian Jiang PeckShield

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring a Computer Science degree in the USA opens up a range of flexible educational routes and career options. For those interested in entering the workforce quickly, quick certifications that pay well can be a smart starting point. These certifications offer practical skills with short-term investments, making them ideal for rapid career advancement or a fast industry switch.

Many students also choose to pursue quick masters degrees online, which allow you to gain specialized knowledge and credentials in less time. Online master’s programs in computer science and related fields are in high demand and can be completed in as little as a year, increasing your chances of landing top roles.

Looking for long-term value? Consider programs highlighted in graduate degrees that are worth it. These degrees often lead to higher salaries and leadership positions in tech.

Alternatively, associates degrees online provide entry-level access to the computer science field, offering flexibility and affordability for those starting their academic journey or balancing work and study.

Best Scientists Citing Xuanzhe Liu

Trending Scientists

Recently Published Articles