World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
38
Citations
5183
World Ranking
8122
National Ranking
2242

Qi Wang 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 Qi Wang 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: 182 publications — 41st percentile

41% of scientists in this discipline score the same or lower.

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

Qi Wang 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 Qi Wang 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: 38 D-Index — 20th percentile

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

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

Overview

Qi Wang is a researcher affiliated with the University of South Carolina in the United States. Their research spans the field of Engineering, with a focus on Electrical and Electronic Engineering, Biomedical Engineering, Materials Chemistry, Molecular Biology, and Atomic and Molecular Physics, and Optics.

Their work primarily addresses topics including Advanced Fiber Optic Sensors, Plasmonic and Surface Plasmon Research, Photonic and Optical Devices, Advanced Biosensing and Bioanalysis Techniques, Gold and Silver Nanoparticles Synthesis and Applications, Analytical Chemistry and Sensors, and Advanced Chemical Sensor Technologies.

Qi Wang's recent publications include:

  • Wearable Sensing and Telehealth Technology with Potential Applications in the Coronavirus Pandemic (2020, IEEE Reviews in Biomedical Engineering)
  • Research advances on surface plasmon resonance biosensors (2021, Nanoscale)
  • Short-Time Wavelet Entropy Integrating Improved LSTM for Fault Diagnosis of Modular Multilevel Converter (2021, IEEE Transactions on Cybernetics)
  • Lab-on-fiber: plasmonic nano-arrays for sensing (2020, Nanoscale)
  • Overview of organic-inorganic hybrid silica aerogels: Progress and perspectives (2022, Materials & Design)

Frequent co-authors collaborating with Qi Wang include Aisong Zhu, Lei Wang, Wan-Ming Zhao, Xiangyu Yin, and Xin Yan.

Qi Wang's research has been published extensively in venues such as SSRN Electronic Journal, IEEE Transactions on Instrumentation and Measurement, arXiv (Cornell University), IEEE Sensors Journal, and Optics & Laser Technology. These venues represent the broad dissemination of their work across multiple specialized journals and platforms.

Best Publications

  • Numerical approximations for the molecular beam epitaxial growth model based on the invariant energy quadratization method

    Xiaofeng Yang;Jia Zhao;Jia Zhao;Qi Wang;Qi Wang

  • Numerical Approximations for a three components Cahn-Hilliard phase-field Model based on the Invariant Energy Quadratization method

    Xiaofeng Yang;Jia Zhao;Jia Zhao;Qi Wang;Qi Wang;Jie Shen

  • Numerical approximations for a phase field dendritic crystal growth model based on the invariant energy quadratization approach

    Jia Zhao;Jia Zhao;Qi Wang;Qi Wang;Xiaofeng Yang

  • Review of mathematical models for biofilms

    Qi Wang;Tianyu Zhang

  • A conservative Fourier pseudo-spectral method for the nonlinear Schrödinger equation

    Yuezheng Gong;Qi Wang;Yushun Wang;Jiaxiang Cai

  • A novel linear second order unconditionally energy stable scheme for a hydrodynamic Q -tensor model of liquid crystals

    Jia Zhao;Jia Zhao;Xiaofeng Yang;Yuezheng Gong;Qi Wang;Qi Wang

  • Bioprinting of a functional vascularized mouse thyroid gland construct

    Elena A Bulanova;Elizaveta V Koudan;Jonathan Degosserie;Charlotte Heymans

  • Phase Field Models for Biofilms. I: theory and One-Dimensional Simulations

    Tianyu Zhang;N. G. Cogan;Qi Wang

  • The weak shear kinetic phase diagram for nematic polymers

    M. Gregory Forest;Qi Wang;Ruhai Zhou

  • A hydrodynamic theory for solutions of nonhomogeneous nematic liquid crystalline polymers of different configurations

    Qi Wang

  • The flow-phase diagram of Doi-Hess theory for sheared nematic polymers II: finite shear rates

    M. Gregory Forest;Qi Wang;Ruhai Zhou

  • Monodomain response of finite-aspect-ratio macromolecules in shear and related linear flows

    M. Gregory Forest;Qi Wang

  • Fully Discrete Second-Order Linear Schemes for Hydrodynamic Phase Field Models of Binary Viscous Fluid Flows with Variable Densities

    Yuezheng Gong;Jia Zhao;Xiaogang Yang;Qi Wang

  • A decoupled energy stable scheme for a hydrodynamic phase-field model of mixtures of nematic liquid crystals and viscous fluids

    Jia Zhao;Xiaofeng Yang;Jie Shen;Qi Wang

  • Energy Stable Numerical Schemes for a Hydrodynamic Model of Nematic Liquid Crystals

    Jia Zhao;Xiaofeng Yang;Jun Li;Qi Wang

  • Energy law preserving C0 finite element schemes for phase field models in two-phase flow computations

    Jinsong Hua;Ping Lin;Chun Liu;Qi Wang

  • Mass and Volume Conservation in Phase Field Models for Binary Fluids

    Jie Shen;Xiaofeng Yang;Qi Wang

  • Arbitrarily high-order linear energy stable schemes for gradient flow models

    Yuezheng Gong;Jia Zhao;Qi Wang

  • Arbitrarily High-Order Unconditionally Energy Stable Schemes for Thermodynamically Consistent Gradient Flow Models

    Yuezheng Gong;Jia Zhao;Qi Wang

  • Modeling fusion of cellular aggregates in biofabrication using phase field theories.

    Xiaofeng Yang;Vladimir Mironov;Qi Wang;Qi Wang

  • Arbitrarily high-order unconditionally energy stable SAV schemes for gradient flow models

    Yuezheng Gong;Jia Zhao;Qi Wang

Frequent Co-Authors

Jie Shen
Jie Shen Eastern Institute of Technology, Ningbo
Chun Liu
Chun Liu Illinois Institute of Technology
Vladimir Mironov
Vladimir Mironov Sechenov University
Jun Li
Jun Li National University of Singapore
Ken Jacobson
Ken Jacobson University of North Carolina at Chapel Hill
Robert E. W. Hancock
Robert E. W. Hancock University of British Columbia
Weinan E
Weinan E Princeton University
Roger R. Markwald
Roger R. Markwald Medical University of South Carolina
Qian Wang
Qian Wang University of South Carolina
Falai Chen
Falai Chen University of Science and Technology of China

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