World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
48
Citations
7551
World Ranking
6252
National Ranking
374

Jie Zhang 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 Zhang 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: 330 publications — 79th percentile

79% of scientists in this discipline score the same or lower.

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

Jie Zhang 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 Zhang 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: 48 D-Index — 58th percentile

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

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

Overview

Jie Zhang is affiliated with Newcastle University in the United Kingdom and has a significant body of work in the field of engineering, with a particular focus on control systems and applied environmental technologies. Their research output spans 265 publications primarily centered on engineering and its applications.

The main subfields of Jie Zhang's expertise include Control and Systems Engineering, Mechanical Engineering, Artificial Intelligence, Biomedical Engineering, and Water Science and Technology. These areas reflect a multidisciplinary approach bridging traditional engineering disciplines with modern technological advancements.

Jie Zhang's research interests cover a range of specific topics, including:

  • Fault Detection and Control Systems
  • Advanced Control Systems Optimization
  • Machine Learning and Extreme Learning Machine (ELM)
  • Adsorption and biosorption for pollutant removal
  • Metallurgical Processes and Thermodynamics
  • Solar-Powered Water Purification Methods
  • Advanced Photocatalysis Techniques

Their recent published papers illustrate a combination of experimental, modeling, and machine learning methodologies applied to environmental and energy-related challenges. Notable recent publications are:

  • "Jujube stones based highly efficient activated carbon for methylene blue adsorption: Kinetics and isotherms modeling, thermodynamics and mechanism study, optimization via response surface methodology and machine learning approaches" (2022), published in Process Safety and Environmental Protection
  • "Optimisation of two-stage biomass gasification for hydrogen production via artificial neural network" (2021), published in Applied Energy
  • "Modeling the organic matter of water using the decision tree coupled with bootstrap aggregated and least-squares boosting" (2022), published in Environmental Technology & Innovation
  • "Milk Source Identification and Milk Quality Estimation Using an Electronic Nose and Machine Learning Techniques" (2020), published in Sensors
  • "Mixed coagulant-flocculant optimization for pharmaceutical effluent pretreatment using response surface methodology and Gaussian process regression" (2022), published in Process Safety and Environmental Protection

Jie Zhang frequently collaborates with several co-authors, including Hichem Tahraoui, Abdeltif Amrane, Mohammed Kebir, Aymen Amine Assadi, and Lotfi Mouni, reflecting a sustained collaborative network in their research endeavors.

Their work has been consistently disseminated through a range of scientific journals, with multiple publications appearing in venues such as:

  • Water
  • Processes
  • Catalysts
  • SSRN Electronic Journal
  • arXiv (Cornell University)

Best Publications

  • Recurrent neuro-fuzzy networks for nonlinear process modeling

    Jie Zhang;A.J. Morris

  • Prediction of water quality index (WQI) using support vector machine (SVM) and least square-support vector machine (LS-SVM)

    Wei Cong Leong;Alireza Bahadori;Jie Zhang;Z. Ahmad

  • Performance monitoring of processes with multiple operating modes through multiple PLS models

    Shi Jian Zhao;Jie Zhang;Yong Mao Xu

  • A batch-to-batch iterative optimal control strategy based on recurrent neural network models

    Zhihua Xiong;Jie Zhang

  • Process performance monitoring using multivariate statistical process control

    E.B. Martin;A.J. Morris;J. Zhang

  • Developing robust non-linear models through bootstrap aggregated neural networks

    Jie Zhang

  • Artificial Intelligence techniques applied as estimator in chemical process systems - A literature survey

    Jarinah Mohd Ali;M.A. Hussain;Moses O. Tade;Jie Zhang

  • Structure-constrained low-rank representation.

    Kewei Tang;Risheng Liu;Zhixun Su;Jie Zhang

  • Inferential Estimation of Polymer Quality Using Stacked Neural Networks

    J. Zhang;E.B. Martin;A.J. Morris;C. Kiparissides

  • A sequential learning approach for single hidden layer neural networks

    Jie Zhang;A. J. Morris

  • Fuzzy neural networks for nonlinear systems modelling

    J. Zhang;A.J. Morris

  • Improved on-line process fault diagnosis through information fusion in multiple neural networks

    Jie Zhang

  • Product Quality Trajectory Tracking in Batch Processes Using Iterative Learning Control Based on Time-Varying Perturbation Models

    Zhihua Xiong;Jie Zhang

  • Batch-to-batch optimal control of a batch polymerisation process based on stacked neural network models

    Jie Zhang

  • Prediction of polymer quality in batch polymerisation reactors using robust neural networks

    J. Zhang;A.J. Morris;E.B. Martin;C. Kiparissides

  • On-line multivariate statistical monitoring of batch processes using Gaussian mixture model

    Tao Chen;Jie Zhang

  • Process monitoring using non-linear statistical techniques

    J Zhang;E.B Martin;A.J Morris

  • Process modelling and fault diagnosis using fuzzy neural networks

    Jie Zhang;Julian Morris

  • SMI 2013: Point cloud normal estimation via low-rank subspace clustering

    Jie Zhang;Junjie Cao;Xiuping Liu;Jun Wang

  • A Reliable Neural Network Model Based Optimal Control Strategy for a Batch Polymerization Reactor

    Jie Zhang

  • Long-term prediction models based on mixed order locally recurrent neural networks

    J. Zhang;A.J. Morris;E.B. Martin

Frequent Co-Authors

A.J. Morris
A.J. Morris University of Newcastle Australia
Karl Herrup
Karl Herrup Hong Kong University of Science and Technology
Huaxi Xu
Huaxi Xu Xiamen University
Guojun Bu
Guojun Bu Hong Kong University of Science and Technology
Alireza Bahadori
Alireza Bahadori Southern Cross University
M. Maral Mouradian
M. Maral Mouradian Rutgers, The State University of New Jersey
Costas Kiparissides
Costas Kiparissides Aristotle University of Thessaloniki
Dorothy E. Vatner
Dorothy E. Vatner Rutgers, The State University of New Jersey
Meihong Wang
Meihong Wang University of Sheffield
Stephen F. Vatner
Stephen F. Vatner Rutgers, The State University of New Jersey

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