World's Best Scientists 2026 revealed!
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Computer Science
Australia
2025

D-Index & Metrics

Computer Science

D-Index
85
Citations
26520
World Ranking
809
National Ranking
18

Jie Lu 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 Jie Lu 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: 709 publications — 98th percentile

98% of scientists in this discipline score the same or lower.

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

Jie Lu 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 Jie Lu 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: 85 D-Index — 94th percentile

94% 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

  • 2025 - Research.com Computer Science in Australia Leader Award
  • 2023 - Research.com Computer Science in Australia Leader Award
  • 2022 - Research.com Computer Science in Australia Leader Award

Overview

Jie Lu is affiliated with the University of Technology Sydney in Australia, specializing primarily in computer science with a focus on artificial intelligence and related subfields. Their research encompasses a range of interdisciplinary topics, notably in machine learning, domain adaptation, and data stream mining techniques.

The main fields and subfields of Ji Lu's work include:

  • Computer Science
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Management Science and Operations Research
  • Electrical and Electronic Engineering

Key research topics covered in their publications are:

  • Data Stream Mining Techniques
  • Domain Adaptation and Few-Shot Learning
  • Machine Learning and Data Classification
  • Multimodal Machine Learning Applications
  • Machine Learning and ELM (Extreme Learning Machine)
  • Anomaly Detection Techniques and Applications
  • Advanced Bandit Algorithms Research

Notable frequent co-authors with productive collaboration counts are:

  • Guangquan Zhang
  • Zhen Fang
  • Junyu Xuan
  • Anjin Liu
  • Qian Zhang

The most common venues for Jie Lu's research outputs include:

  • arXiv (Cornell University)
  • IEEE Transactions on Cybernetics
  • IEEE Transactions on Neural Networks and Learning Systems
  • IEEE Transactions on Fuzzy Systems
  • SSRN Electronic Journal

Among recent papers authored or co-authored by Jie Lu are:

  • Gesture recognition using a bioinspired learning architecture that integrates visual data with somatosensory data from stretchable sensors, 2020, Nature Electronics
  • Artificial intelligence in recommender systems, 2020, Complex & Intelligent Systems
  • Open Set Domain Adaptation: Theoretical Bound and Algorithm, 2020, IEEE Transactions on Neural Networks and Learning Systems
  • Heterogeneous Domain Adaptation: An Unsupervised Approach, 2020, IEEE Transactions on Neural Networks and Learning Systems
  • Multisource Heterogeneous Unsupervised Domain Adaptation via Fuzzy Relation Neural Networks, 2020, IEEE Transactions on Fuzzy Systems

In addition to journal papers, Jie Lu has contributed to books published by notable academic publishers. These include three titles under Springer Nature:

  • Recent Advances in Artificial Intelligence and Data Engineering, 2021
  • Educating Engineers for Future Industrial Revolutions, 2021
  • Intelligent Computing and Applications, 2020

Additionally, Jie Lu authored a book published by World Scientific:

  • Recommender Systems, 2020

Best Publications

  • Recommender system application developments

    Jie Lu;Dianshuang Wu;Mingsong Mao;Wei Wang

  • Learning under Concept Drift: A Review

    Jie Lu;Anjin Liu;Fan Dong;Feng Gu

  • Transfer learning using computational intelligence

    Jie Lu;Vahid Behbood;Peng Hao;Hua Zuo

  • Tunable lifetime multiplexing using luminescent nanocrystals

    Yiqing Lu;Jiangbo Zhao;Run Zhang;Yujia Liu;Yujia Liu;Yujia Liu

  • Multi-objective Group Decision Making: Methods, Software and Applications With Fuzzy Set Techniques

    Jie Lu;Guangquan Zhang;Da Ruan

  • Gesture recognition using a bioinspired learning architecture that integrates visual data with somatosensory data from stretchable sensors

    Ming Wang;Zheng Yan;Ting Wang;Pingqiang Cai

  • Artificial intelligence in recommender systems

    Qian Zhang;Jie Lu;Yaochu Jin

  • Task-Based System Load Balancing in Cloud Computing Using Particle Swarm Optimization

    Fahimeh Ramezani;Jie Lu;Farookh Khadeer Hussain

  • A Kernel Fuzzy c-Means Clustering-Based Fuzzy Support Vector Machine Algorithm for Classification Problems With Outliers or Noises

    Xiaowei Yang;Guangquan Zhang;Jie Lu;Jun Ma

  • Multi-Objective Group Decision Making: Methods, Software and Applications with Fuzzy Set Techniques(With CD-ROM)

    Jie Lu;Guangquan Zhang;Da Ruan;Fengjie Wu

  • A Personalized e-Learning material Recommender System

    J Lu

  • A Customer Churn Prediction Model in Telecom Industry Using Boosting

    Ning Lu;Hua Lin;Jie Lu;Guangquan Zhang

  • Ontology-supported case-based reasoning approach for intelligent m-Government emergency response services

    Khaled Amailef;Jie Lu

  • A hybrid fuzzy-based personalized recommender system for telecom products/services

    Zui Zhang;Hua Lin;Kun Liu;Dianshuang Wu

  • Operation properties and δ-equalities of complex fuzzy sets

    Guangquan Zhang;Tharam Singh Dillon;Kai-Yuan Cai;Jun Ma

  • Concept drift detection via competence models

    Ning Lu;Guangquan Zhang;Jie Lu

  • Topic analysis and forecasting for science, technology and innovation: Methodology with a case study focusing on big data research

    Yi Zhang;Yi Zhang;Guangquan Zhang;Hongshu Chen;Hongshu Chen;Alan L. Porter

  • An extended Kuhn-Tucker approach for linear bilevel programming

    Chenggen Shi;Jie Lu;Guangquan Zhang

  • On-the-fly decoding luminescence lifetimes in the microsecond region for lanthanide-encoded suspension arrays

    Yiqing Lu;Jie Lu;Jiangbo Zhao;Janet Cusido

  • A trust-semantic fusion-based recommendation approach for e-business applications

    Qusai Shambour;Jie Lu

  • Decider: A fuzzy multi-criteria group decision support system

    Jun Ma;Jie Lu;Guangquan Zhang

Frequent Co-Authors

Guangquan Zhang
Guangquan Zhang University of Technology Sydney
Jun Ma
Jun Ma Harbin Institute of Technology
Da Ruan
Da Ruan Ghent University
Xiangfeng Luo
Xiangfeng Luo Shanghai University
Farookh Khadeer Hussain
Farookh Khadeer Hussain University of Technology Sydney
Tharam S. Dillon
Tharam S. Dillon La Trobe University
Haiyan Lu
Haiyan Lu University of Technology Sydney
Dayong Jin
Dayong Jin University of Technology Sydney
Witold Pedrycz
Witold Pedrycz University of Alberta
Zheng Yan
Zheng Yan Xidian University

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