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Ting 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 Ting 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+

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

Ting 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 Ting 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+

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

Overview

Ting Wang is affiliated with Nanyang Technological University in Singapore and focuses their research primarily within the field of Engineering. Their work spans several subfields, including Electrical and Electronic Engineering, Control and Systems Engineering, Civil and Structural Engineering, Building and Construction, and Biomedical Engineering.

Their research covers a range of topics with significant contributions in HVDC Systems and Fault Protection, Microgrid Control and Optimization, Power Systems Fault Detection, Recycled Aggregate Concrete Performance, Innovative Concrete Reinforcement Materials, Advanced Memory and Neural Computing, and Smart Grid Security and Resilience.

Ting Wang has published in various journals and venues, with frequent appearances in the following publication venues:

  • SSRN Electronic Journal
  • IEEE Transactions on Power Delivery
  • Advanced Materials
  • International Journal of Electrical Power & Energy Systems
  • REVIEWS ON ADVANCED MATERIALS SCIENCE

Among recent notable papers, Ting Wang is the author of the 2022 publication titled A chemically mediated artificial neuron in Nature Electronics. Other selected recent works from their research area include:

  • Portable Food-Freshness Prediction Platform Based on Colorimetric Barcode Combinatorics and Deep Convolutional Neural Networks, 2020, Advanced Materials
  • Artificial Neural Pathway Based on a Memristor Synapse for Optically Mediated Motion Learning, 2022, ACS Nano
  • Tactile Near-Sensor Analogue Computing for Ultrafast Responsive Artificial Skin, 2022, Advanced Materials
  • Thermal analysis and management of proton exchange membrane fuel cell stacks for automotive vehicle, 2021, International Journal of Hydrogen Energy

The scientist collaborates frequently with other researchers, having co-authored multiple papers with colleagues such as Antonello Monti, Zhiguo Hao, Tian Su, Ferdinanda Ponci, and Xiaodong Chen.

Best Publications

  • 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

  • 3D Printed Photoresponsive Devices Based on Shape Memory Composites

    Hui Yang;Wan Ru Leow;Ting Wang;Juan Wang

  • Synthesis of Core–Shell Magnetic Fe3O4@poly(m-Phenylenediamine) Particles for Chromium Reduction and Adsorption

    Ting Wang;Liyuan Zhang;Chaofang Li;Weichun Yang

  • Flexible Transparent Electronic Gas Sensors.

    Ting Wang;Ting Wang;Yunlong Guo;Pengbo Wan;Han Zhang

  • Artificial Skin Perception.

    Ming Wang;Yifei Luo;Ting Wang;Changjin Wan

  • Portable Food-Freshness Prediction Platform Based on Colorimetric Barcode Combinatorics and Deep Convolutional Neural Networks

    Lingling Guo;Ting Wang;Zhonghua Wu;Jianwu Wang

  • Soft Thermal Sensor with Mechanical Adaptability.

    Hui Yang;Dianpeng Qi;Zhiyuan Liu;Bevita K. Chandran

  • Water-Resistant Conformal Hybrid Electrodes for Aquatic Endurable Electrocardiographic Monitoring

    Shaobo Ji;Changjin Wan;Ting Wang;Qingsong Li

  • Controllable Synthesis of Hierarchical Porous Fe3O4 Particles Mediated by Poly(diallyldimethylammonium chloride) and Their Application in Arsenic Removal

    Ting Wang;Liyuan Zhang;Haiying Wang;Weichun Yang

  • Hierarchical graphene–polyaniline nanocomposite films for high-performance flexible electronic gas sensors

    Yunlong Guo;Ting Wang;Fanhong Chen;Xiaoming Sun

  • A compliant ionic adhesive electrode with ultralow bioelectronic impedance

    Liang Pan;Pingqiang Cai;Le Mei;Yuan Cheng

  • Silver nanoparticle-decorated carbon nanotubes as bifunctional gas-diffusion electrodes for zinc–air batteries

    T. Wang;M. Kaempgen;P. Nopphawan;G. Wee

  • Adhesive Biocomposite Electrodes on Sweaty Skin for Long-Term Continuous Electrophysiological Monitoring

    Hui Yang;Shaobo Ji;Iti Chaturvedi;Huarong Xia

  • Preparation of a macroscopic, robust carbon-fiber monolith from filamentous fungi and its application in Li–S batteries

    Liyuan Zhang;Yangyang Wang;Bing Peng;Wanting Yu

  • Full microwave synthesis of advanced Li-rich manganese based cathode material for lithium ion batteries

    Shaojun Shi;Saisai Zhang;Zhijun Wu;Ting Wang

  • Porous Hybrid Composites of Few‐Layer MoS2 Nanosheets Embedded in a Carbon Matrix with an Excellent Supercapacitor Electrode Performance

    Hongmei Ji;Hongmei Ji;Chao Liu;Ting Wang;Jing Chen

  • Facile synthesis of Fe3O4@Cu(OH)2 composites and their arsenic adsorption application

    Bing Peng;Tingting Song;Ting Wang;Liyuan Chai

  • Fusing Stretchable Sensing Technology with Machine Learning for Human–Machine Interfaces

    Ming Wang;Ting Wang;Yifei Luo;Ke He

  • Mechano‐Based Transductive Sensing for Wearable Healthcare

    Ting Wang;Ting Wang;Hui Yang;Dianpeng Qi;Zhiyuan Liu

  • A flexible transparent colorimetric wrist strap sensor

    Ting Wang;Ting Wang;Ting Wang;Yunlong Guo;Pengbo Wan;Xiaoming Sun

Frequent Co-Authors

Xiaodong Chen
Xiaodong Chen Nanyang Technological University
Gang Yang
Gang Yang Changshu Institute of Technology
Qingji Xie
Qingji Xie Hunan Normal University
Zhiyuan Liu
Zhiyuan Liu Shenzhen Institutes of Advanced Technology
Dianpeng Qi
Dianpeng Qi Harbin Institute of Technology
Han Zhang
Han Zhang Shenzhen University
Jinhua Chen
Jinhua Chen Hunan University
Xiaoming Sun
Xiaoming Sun Beijing University of Chemical Technology
Pengbo Wan
Pengbo Wan Beijing University of Chemical Technology
Chuanlai Xu
Chuanlai Xu Jiangnan University

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