World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
59
Citations
15086
World Ranking
1724
National Ranking
288

Qing Wan publication distribution in Electronics and Electrical Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Electronics and Electrical Engineering in 2026. The highlighted bar marks where Qing Wan sits on this spectrum.

34–53 publications: 24 scientists 54–73 publications: 52 scientists 74–93 publications: 114 scientists 94–113 publications: 203 scientists 114–133 publications: 269 scientists 134–153 publications: 355 scientists 154–173 publications: 403 scientists 174–193 publications: 445 scientists 194–213 publications: 430 scientists 214–233 publications: 431 scientists 234–253 publications: 399 scientists 254–273 publications: 366 scientists 274–293 publications: 335 scientists 294–313 publications: 300 scientists 314–333 publications: 276 scientists 334–353 publications: 250 scientists 354–373 publications: 214 scientists 374–393 publications: 187 scientists 394–413 publications: 152 scientists 414–433 publications: 169 scientists 434–453 publications: 147 scientists 454–473 publications: 111 scientists 474–493 publications: 117 scientists 494–513 publications: 103 scientists 514–533 publications: 99 scientists 534–553 publications: 92 scientists 554–573 publications: 75 scientists 574–593 publications: 58 scientists 594–613 publications: 69 scientists 614–633 publications: 50 scientists 634–653 publications: 62 scientists 654–673 publications: 54 scientists 674–693 publications: 44 scientists 694–713 publications: 37 scientists 714–733 publications: 28 scientists 734–753 publications: 26 scientists 754–773 publications: 26 scientists 774–793 publications: 19 scientists 794–813 publications: 23 scientists 814–833 publications: 20 scientists 834–853 publications: 16 scientists 854–873 publications: 20 scientists 874–893 publications: 11 scientists 894–913 publications: 11 scientists 914–933 publications: 16 scientists 934–953 publications: 13 scientists 954–973 publications: 10 scientists 974–993 publications: 11 scientists 994–1,013 publications: 9 scientists 1,014–1,033 publications: 9 scientists 1,034–1,053 publications: 10 scientists 1,054–1,064 publications: 6 scientists 1,065+ publications: 99 scientists
34 publications 1,065+

This scientist: 249 publications — 44th percentile

44% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,065 publications or more.

Qing Wan D-index placement in Electronics and Electrical Engineering in 2026

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

30 D-Index: 178 scientists 31 D-Index: 257 scientists 32 D-Index: 263 scientists 33 D-Index: 262 scientists 34 D-Index: 244 scientists 35 D-Index: 236 scientists 36 D-Index: 211 scientists 37 D-Index: 220 scientists 38 D-Index: 214 scientists 39 D-Index: 214 scientists 40 D-Index: 205 scientists 41 D-Index: 187 scientists 42 D-Index: 194 scientists 43 D-Index: 201 scientists 44 D-Index: 155 scientists 45 D-Index: 189 scientists 46 D-Index: 148 scientists 47 D-Index: 160 scientists 48 D-Index: 134 scientists 49 D-Index: 130 scientists 50 D-Index: 141 scientists 51 D-Index: 156 scientists 52 D-Index: 108 scientists 53 D-Index: 130 scientists 54 D-Index: 112 scientists 55 D-Index: 97 scientists 56 D-Index: 111 scientists 57 D-Index: 102 scientists 58 D-Index: 108 scientists 59 D-Index: 120 scientists 60 D-Index: 103 scientists 61 D-Index: 93 scientists 62 D-Index: 92 scientists 63 D-Index: 74 scientists 64 D-Index: 77 scientists 65 D-Index: 73 scientists 66 D-Index: 64 scientists 67 D-Index: 69 scientists 68 D-Index: 60 scientists 69 D-Index: 39 scientists 70 D-Index: 57 scientists 71 D-Index: 59 scientists 72 D-Index: 46 scientists 73 D-Index: 49 scientists 74 D-Index: 38 scientists 75 D-Index: 35 scientists 76 D-Index: 32 scientists 77 D-Index: 35 scientists 78 D-Index: 31 scientists 79 D-Index: 22 scientists 80 D-Index: 34 scientists 81 D-Index: 31 scientists 82 D-Index: 34 scientists 83 D-Index: 23 scientists 84 D-Index: 18 scientists 85 D-Index: 30 scientists 86 D-Index: 19 scientists 87 D-Index: 19 scientists 88 D-Index: 20 scientists 89 D-Index: 8 scientists 90 D-Index: 17 scientists 91 D-Index: 7 scientists 92 D-Index: 14 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 12 scientists 97 D-Index: 10 scientists 98 D-Index: 10 scientists 99 D-Index: 12 scientists 100 D-Index: 16 scientists 101 D-Index: 5 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 8 scientists 105 D-Index: 9 scientists 106 D-Index: 13 scientists 107 D-Index: 4 scientists 108 D-Index: 5 scientists 109 D-Index: 10 scientists 110 D-Index: 8 scientists 111+ D-Index: 96 scientists
30 D-Index 111+

This scientist: 59 D-Index — 75th percentile

75% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 111 D-Index or more.

Overview

Qing Wan is affiliated with Nanjing University in China and conducts research primarily in the field of engineering, with a focus on electrical and electronic engineering. Their body of work includes investigations spanning multiple subfields such as cellular and molecular neuroscience, biomedical engineering, materials chemistry, and artificial intelligence.

The scientist's research covers topics including advanced memory and neural computing, neuroscience and neural engineering, photoreceptor and optogenetics research, ferroelectric and negative capacitance devices, neural networks and reservoir computing, nanoplatforms for cancer theranostics, and neural dynamics and brain function.

Qing Wan has contributed to several recent papers, including:

  • Smartphone-Based Electrochemical Immunoassay for Point-of-Care Detection of SARS-CoV-2 Nucleocapsid Protein, 2022, Analytical Chemistry
  • Flexible Vertical Photogating Transistor Network with an Ultrashort Channel for In-Sensor Visual Nociceptor, 2021, Advanced Functional Materials
  • A Photoelectric Spiking Neuron for Visual Depth Perception, 2022, Advanced Materials
  • Indium-gallium-zinc-oxide thin-film transistors: Materials, devices, and applications, 2021, Journal of Semiconductors
  • Recent Progress on Emerging Transistor-Based Neuromorphic Devices, 2021, Advanced Intelligent Systems

Frequent collaborators include Chunsheng Chen, Li Zhu, Changjin Wan, Ying Zhu, and Yongli He. These coauthors have worked with Qing Wan on numerous publications, with collaboration counts ranging around 15 to 19 joint works.

The scientist publishes often in established venues such as IEEE Transactions on Electron Devices, IEEE Electron Device Letters, Advanced Materials, Journal of Physics D Applied Physics, and the Sixth International Conference on Traffic Engineering and Transportation System (ICTETS 2022).

Best Publications

  • Fabrication and ethanol sensing characteristics of ZnO nanowire gas sensors

    Q. Wan;Q. H. Li;Y. J. Chen;T. H. Wang

  • Artificial synapse network on inorganic proton conductor for neuromorphic systems

    Li Qiang Zhu;Chang Jin Wan;Li Qiang Guo;Yi Shi

  • A MoS 2 /PTCDA Hybrid Heterojunction Synapse with Efficient Photoelectric Dual Modulation and Versatility

    Shuiyuan Wang;Chunsheng Chen;Zhihao Yu;Yongli He

  • Freestanding Artificial Synapses Based on Laterally Proton‐Coupled Transistors on Chitosan Membranes

    Yang Hui Liu;Yang Hui Liu;Li Qiang Zhu;Li Qiang Zhu;Ping Feng;Yi Shi

  • An Artificial Sensory Neuron with Tactile Perceptual Learning.

    Changjin Wan;Geng Chen;Yangming Fu;Ming Wang

  • Low-field electron emission from tetrapod-like ZnO nanostructures synthesized by rapid evaporation

    Q. Wan;K. Yu;T. H. Wang;C. L. Lin

  • Fully transparent thin-film transistor devices based on SnO2 nanowires.

    Eric N. Dattoli;Qing Wan;Wei Guo;Yanbin Chen

  • Electronic transport through individual ZnO nanowires

    Q. H. Li;Q. Wan;Y. X. Liang;T. H. Wang

  • Contact-controlled sensing properties of flowerlike ZnO nanostructures

    P. Feng;Q. Wan;T. H. Wang

  • 2D MoS 2 Neuromorphic Devices for Brain-Like Computational Systems.

    Jie Jiang;Junjie Guo;Xiang Wan;Xiang Wan;Yi Yang;Yi Yang

  • 2D electric-double-layer phototransistor for photoelectronic and spatiotemporal hybrid neuromorphic integration

    Jie Jiang;Wennan Hu;Dingdong Xie;Junliang Yang

  • Proton-Conducting Graphene Oxide-Coupled Neuron Transistors for Brain-Inspired Cognitive Systems.

    Chang Jin Wan;Chang Jin Wan;Li Qiang Zhu;Yang Hui Liu;Ping Feng

  • Electric-double-layer transistors for synaptic devices and neuromorphic systems

    Yongli He;Yi Yang;Sha Nie;Rui Liu

  • A light-stimulated synaptic device based on graphene hybrid phototransistor

    Shuchao Qin;Fengqiu Wang;Yujie Liu;Qing Wan

  • Spatiotemporal Information Processing Emulated by Multiterminal Neuro-Transistor Networks.

    Yongli He;Sha Nie;Rui Liu;Shanshan Jiang

  • Artificial Synapses Based on in-Plane Gate Organic Electrochemical Transistors

    Chuan Qian;Jia Sun;Ling-an Kong;Guangyang Gou

  • Printed Neuromorphic Devices Based on Printed Carbon Nanotube Thin-Film Transistors

    Ping Feng;Weiwei Xu;Yi Yang;Xiang Wan

  • Transparent metallic Sb-doped SnO2 nanowires

    Qing Wan;Eric N. Dattoli;Wei Lu

  • integrations and challenges of novel high-k gate stacks in advanced cmos technology

    Gang He;Gang He;Liqiang Zhu;Zhaoqi Sun;Qing Wan

  • A Sub-10 nm Vertical Organic/Inorganic Hybrid Transistor for Pain-Perceptual and Sensitization-Regulated Nociceptor Emulation.

    Guangdi Feng;Jie Jiang;Yuhang Zhao;Shitan Wang

  • Flexible Metal Oxide/Graphene Oxide Hybrid Neuromorphic Transistors on Flexible Conducting Graphene Substrates.

    Chang Jin Wan;Chang Jin Wan;Yang Hui Liu;Ping Feng;Wei Wang;Wei Wang

  • Energy-Efficient Artificial Synapses Based on Flexible IGZO Electric-Double-Layer Transistors

    Jumei Zhou;Ning Liu;Liqiang Zhu;Yi Shi

  • Artificial Synaptic Devices Based on Natural Chicken Albumen Coupled Electric-Double-Layer Transistors

    Guodong Wu;Ping Feng;Xiang Wan;Liqiang Zhu

  • Flexible Vertical Photogating Transistor Network with an Ultrashort Channel for In-Sensor Visual Nociceptor

    Guangdi Feng;Guangdi Feng;Jie Jiang;Yanran Li;Dingdong Xie

  • Organic synaptic devices for neuromorphic systems

    Jia Sun;Ying Fu;Qing Wan

  • Flexible Neuromorphic Architectures Based on Self-Supported Multiterminal Organic Transistors.

    Ying Fu;Ling-an Kong;Yang Chen;Juxiang Wang

  • Long-Term Synaptic Plasticity Emulated in Modified Graphene Oxide Electrolyte Gated IZO-Based Thin-Film Transistors

    Yi Yang;Juan Wen;Liqiang Guo;Xiang Wan

  • Gas Sensors Based on Semiconducting Nanowire Field-Effect Transistors

    Ping Feng;Feng Shao;Yi Shi;Qing Wan

  • Light Stimulated IGZO-Based Electric-Double-Layer Transistors For Photoelectric Neuromorphic Devices

    Yi Yang;Yongli He;Sha Nie;Yi Shi

Frequent Co-Authors

Yi Shi
Yi Shi Nanjing University
Li Qiang Zhu
Li Qiang Zhu Ningbo University
Yongli Gao
Yongli Gao University of Rochester
Junliang Yang
Junliang Yang Central South University
Jie Jiang
Jie Jiang Central South University
Jun He
Jun He Central South University
Lijia Pan
Lijia Pan Nanjing University
Jia Sun
Jia Sun Central South University
Xinran Wang
Xinran Wang Nanjing University
Xiaodong Chen
Xiaodong Chen Nanyang Technological University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

For students interested in Electronics and Electrical Engineering, exploring related online degrees can open diverse career pathways. Programs such as the best online teaching master's programs offer advanced knowledge for those looking to transition into education or training roles within engineering fields. These degrees emphasize both technical expertise and instructional skills, ideal for career growth in academia or corporate training.

Competency-based learning is becoming increasingly popular, especially in technical fields. Competency-based master’s programs focus on mastering specific skills at your own pace, making them a flexible option for working professionals or those balancing family commitments. Programs highlighted under competency based masters can provide targeted advancement in engineering disciplines without the constraints of traditional timelines.

Online education platforms are also especially supportive of military families. Many institutions cater to military spouses and dependents, helping them achieve their educational goals with minimal disruption. Check out options tailored for military personnel in the military spouse online college category to find programs designed for flexibility and accessibility.

Finally, schools offering the best online colleges with weekly start dates provide even greater flexibility, enabling students to begin their studies at a time that suits their schedule. This flexibility is invaluable for those balancing work, family, or other commitments while advancing their engineering education online.

Best Scientists Citing Qing Wan

Trending Scientists

Recently Published Articles