World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
53
Citations
12447
World Ranking
3355
National Ranking
138

Ning Jiang publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Ning Jiang sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 335 publications — 82nd percentile

82% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Ning Jiang D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Ning Jiang sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 53 D-Index — 66th percentile

66% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Ning Jiang is affiliated with the University of Waterloo in Canada. Their research spans neuroscience and engineering, with a significant focus on cognitive neuroscience and biomedical engineering. They have contributed extensively to the study of human-computer interaction, cellular and molecular neuroscience, and neurology. Their work frequently explores areas related to muscle activation, electrophysiological methods, and brain-computer interfaces.

The scientist's main research topics include EEG and brain-computer interfaces, muscle activation and electromyography studies, neuroscience and neural engineering, advanced sensor and energy harvesting materials, functional brain connectivity studies, neural dynamics and brain function, and hand gesture recognition systems. Their interdisciplinary approach integrates neural engineering techniques with practical applications in prosthetics and sensor technology.

Ning Jiang has published in numerous venues, notably including IEEE Transactions on Neural Systems and Rehabilitation Engineering, arXiv (Cornell University), The Journal of Immunology, Journal of Neural Engineering, and Frontiers in Aging Neuroscience. These platforms indicate a blend of engineering, immunological, and neuroscience perspectives within their body of work.

  • IEEE Transactions on Neural Systems and Rehabilitation Engineering
  • arXiv (Cornell University)
  • The Journal of Immunology
  • Journal of Neural Engineering
  • Frontiers in Aging Neuroscience

Frequent collaborators in their research include Jiayuan He, Ashirbad Pradhan, Zhiwei Guo, Dario Farina, and Xin Zhang. These coauthors have contributed to a range of investigations related to electromyography, neural interfaces, and related biomedical technologies.

  • Jiayuan He
  • Ashirbad Pradhan
  • Zhiwei Guo
  • Dario Farina
  • Xin Zhang

Notable publications by Ning Jiang and colleagues include:

  • Comparing user-dependent and user-independent training of CNN for SSVEP BCI, 2020, Journal of Neural Engineering
  • Bio-robotics research for non-invasive myoelectric neural interfaces for upper-limb prosthetic control: a 10-year perspective review, 2023, National Science Review
  • Biometric From Surface Electromyogram (sEMG): Feasibility of User Verification and Identification Based on Gesture Recognition, 2020, Frontiers in Bioengineering and Biotechnology
  • MuscleNET: mapping electromyography to kinematic and dynamic biomechanical variables by machine learning, 2021, Journal of Neural Engineering
  • Multi-day dataset of forearm and wrist electromyogram for hand gesture recognition and biometrics, 2022, Scientific Data

Best Publications

  • The Extraction of Neural Information from the Surface EMG for the Control of Upper-Limb Prostheses: Emerging Avenues and Challenges

    Dario Farina;Ning Jiang;Hubertus Rehbaum;Ales Holobar

  • Myoelectric Control of Artificial Limbs—Is There a Need to Change Focus? [In the Spotlight]

    Ning Jiang;S. Dosen;K-R Muller;D. Farina

  • Extracting Simultaneous and Proportional Neural Control Information for Multiple-DOF Prostheses From the Surface Electromyographic Signal

    Ning Jiang;K.B. Englehart;P.A. Parker

  • Linear and Nonlinear Regression Techniques for Simultaneous and Proportional Myoelectric Control

    J. M. Hahne;F. Biebmann;N. Jiang;H. Rehbaum

  • Man/machine interface based on the discharge timings of spinal motor neurons after targeted muscle reinnervation

    Dario Farina;Dario Farina;Ivan Vujaklija;Ivan Vujaklija;Massimo Sartori;Tamás Kapelner

  • Intuitive, Online, Simultaneous, and Proportional Myoelectric Control Over Two Degrees-of-Freedom in Upper Limb Amputees

    Ning Jiang;Hubertus Rehbaum;Ivan Vujaklija;Bernhard Graimann

  • Detection of movement intention from single-trial movement-related cortical potentials

    Imran Khan Niazi;Ning Jiang;Olivier Tiberghien;Jørgen Feldbæk Nielsen

  • Simultaneous and Proportional Force Estimation for Multifunction Myoelectric Prostheses Using Mirrored Bilateral Training

    Johnny L G Nielsen;S Holmgaard;Ning Jiang;K B Englehart

  • Is Accurate Mapping of EMG Signals on Kinematics Needed for Precise Online Myoelectric Control

    Ning Jiang;Ivan Vujaklija;Hubertus Rehbaum;Bernhard Graimann

  • Efficient neuroplasticity induction in chronic stroke patients by an associative brain-computer interface

    Natalie Mrachacz-Kersting;Ning Jiang;Andrew James Thomas Stevenson;Imran Khan Niazi

  • Enhanced Low-Latency Detection of Motor Intention From EEG for Closed-Loop Brain-Computer Interface Applications

    Ren Xu;Ning Jiang;Chuang Lin;Natalie Mrachacz-Kersting

  • EMG-based simultaneous and proportional estimation of wrist/hand kinematics in uni-lateral trans-radial amputees

    Ning Jiang;Johnny Luther Gredal Vest-Nielsen;Silvia Muceli;Silvia Muceli;Dario Farina

  • Myoelectric Control of Artificial Limbs— Is There a Need to Change Focus?

    Ning Jiang;Strahinja Dosen;Klaus-Robert Müller;Dario Farina

  • Self-Correcting Pattern Recognition System of Surface EMG Signals for Upper Limb Prosthesis Control

    Sebastian Amsuss;Peter M. Goebel;Ning Jiang;Bernhard Graimann

  • A Closed-Loop Brain–Computer Interface Triggering an Active Ankle–Foot Orthosis for Inducing Cortical Neural Plasticity

    Ren Xu;Ning Jiang;Natalie Mrachacz-Kersting;Chuang Lin

  • Extracting Signals Robust to Electrode Number and Shift for Online Simultaneous and Proportional Myoelectric Control by Factorization Algorithms

    Silvia Muceli;Ning Jiang;Dario Farina

  • Influence of the training set on the accuracy of surface EMG classification in dynamic contractions for the control of multifunction prostheses

    Thomas Lorrain;Ning Jiang;Dario Farina

  • User adaptation in long-term, open-loop myoelectric training: implications for EMG pattern recognition in prosthesis control.

    Jiayuan He;Dingguo Zhang;Ning Jiang;Xinjun Sheng

  • Physical secure optical communication based on private chaotic spectral phase encryption/decryption.

    Ning Jiang;Anke Zhao;Chenpeng Xue;Jianming Tang

  • Peripheral Electrical Stimulation Triggered by Self-Paced Detection of Motor Intention Enhances Motor Evoked Potentials

    I. K. Niazi;N. Mrachacz-Kersting;Ning Jiang;K. Dremstrup

  • A brain-computer interface for single-trial detection of gait initiation from movement related cortical potentials

    Ning Jiang;Leonardo Gizzi;Natalie Mrachacz-Kersting;Kim Dremstrup

Frequent Co-Authors

Dario Farina
Dario Farina Imperial College London
Kun Qiu
Kun Qiu University of Electronic Science and Technology of China
Wei Pan
Wei Pan Southwest Jiaotong University
Bin Luo
Bin Luo Southwest Jiaotong University
Xiangyang Zhu
Xiangyang Zhu Shanghai Jiao Tong University
Lianshan Yan
Lianshan Yan Southwest Jiaotong University
Xihua Zou
Xihua Zou Southwest Jiaotong University
Kevin Englehart
Kevin Englehart University of New Brunswick
Bernhard Graimann
Bernhard Graimann Graz University of Technology
Philip A. Parker
Philip A. Parker University of New Brunswick

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