World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
56
Citations
16613
World Ranking
2028
National Ranking
797

Computer Science

D-Index
57
Citations
17010
World Ranking
3768
National Ranking
1800

Qing Zhao 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 Zhao 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: 201 publications — 30th percentile

30% of scientists in this discipline score the same or lower.

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

Qing Zhao 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 Zhao 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: 56 D-Index — 71st percentile

71% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2013 - IEEE Fellow For contributions to learning and decision theory in dynamic systems with applications to cognitive networking

Overview

Qing Zhao is affiliated with Cornell University in the United States and has contributed to several fields within computer science and engineering. Their main research areas focus on computer networks and communications, electrical and electronic engineering, and aerospace engineering. The primary domains of study include energy efficient wireless sensor networks, energy harvesting in wireless networks, security in wireless sensor networks, IoT and edge/fog computing, UAV applications and optimization, video surveillance and tracking methods, and age of information optimization.

Their recent publications include the following:

  • Energy Balanced Source Location Privacy Scheme Using Multibranch Path in WSNs for IoT, 2021, Wireless Communications and Mobile Computing
  • Energy-Efficient Opportunistic Routing Algorithm for Post-disaster Mine Internet of Things Networks, 2023, Preprints.org
  • Uav trajectory optimization for maximizing the ToI-based data utility in wireless sensor networks, 2025, Journal of Combinatorial Optimization
  • Research on reliable communication network for data concurrent transmission based on intelligent network connection system, 2021, Journal of Physics Conference Series
  • Table of Contents, 2020, IEEE Signal Processing Magazine

Frequent co-authors who collaborated with Qing Zhao include:

  • Zhen Li
  • Jianqiang Li
  • Jianxiong Guo
  • Xingjian Ding
  • Deying Li

Qing Zhao has published multiple papers in venues such as:

  • Wireless Communications and Mobile Computing
  • Journal of Combinatorial Optimization
  • Preprints.org
  • Journal of Physics Conference Series
  • IEEE Signal Processing Magazine

Their work primarily spans 11 publications within computer science and 4 publications in engineering. The detailed subfields include 10 publications in computer networks and communications, 3 in electrical and electronic engineering, 1 in aerospace engineering, and 1 in computer vision and pattern recognition.

Among recognized honors, Qing Zhao was named IEEE Fellow in 2013 for contributions to learning and decision theory in dynamic systems with applications to cognitive networking.

Best Publications

  • A Survey of Dynamic Spectrum Access

    Qing Zhao;B.M. Sadler

  • Decentralized cognitive MAC for opportunistic spectrum access in ad hoc networks: A POMDP framework

    Qing Zhao;Lang Tong;Ananthram Swami;Yunxia Chen

  • On the lifetime of wireless sensor networks

    Yunxia Chen;Qing Zhao

  • Joint Design and Separation Principle for Opportunistic Spectrum Access in the Presence of Sensing Errors

    Yunxia Chen;Qing Zhao;A. Swami

  • Sensor networks with mobile agents

    Lang Tong;Qing Zhao;S. Adireddy

  • Decentralized cognitive mac for dynamic spectrum access

    Q. Zhao;L. Tong;A. Swami

  • Distributed Learning in Multi-Armed Bandit With Multiple Players

    Keqin Liu;Qing Zhao

  • Optimality of Myopic Sensing in Multichannel Opportunistic Access

    S. Ahmad;Mingyan Liu;T. Javidi;Qing Zhao

  • On myopic sensing for multi-channel opportunistic access: structure, optimality, and performance

    Qing Zhao;B. Krishnamachari;Keqin Liu

  • Indexability of Restless Bandit Problems and Optimality of Whittle Index for Dynamic Multichannel Access

    Keqin Liu;Qing Zhao

  • Multipacket reception in random access wireless networks: from signal processing to optimal medium access control

    Lang Tong;Qing Zhao;G. Mergen

  • A Survey of Dynamic Spectrum Access: Signal Processing and Networking Perspectives

    Qing Zhao;A. Swami

  • Decentralized dynamic spectrum access for cognitive radios: cooperative design of a non-cooperative game

    M. Maskery;V. Krishnamurthy;Qing Zhao

  • Distributed Spectrum Sensing and Access in Cognitive Radio Networks With Energy Constraint

    Yunxia Chen;Qing Zhao;A. Swami

  • A Decision-Theoretic Framework for Opportunistic Spectrum Access

    Qing Zhao;A. Swami

  • Power control in cognitive radio networks: how to cross a multi-lane highway

    Wei Ren;Qing Zhao;A. Swami

  • Learning in a Changing World: Restless Multiarmed Bandit With Unknown Dynamics

    Haoyang Liu;Keqin Liu;Qing Zhao

  • Transmission Scheduling for Optimizing Sensor Network Lifetime: A Stochastic Shortest Path Approach

    Yunxia Chen;Qing Zhao;V. Krishnamurthy;D. Djonin

  • A multiqueue service room MAC protocol for wireless networks with multipacket reception

    Qing Zhao;Lang Tong

  • Optimality of Myopic Sensing in Multi-Channel Opportunistic Access

    T. Javidi;B. Krishnamachari;Qing Zhao;Mingyan Liu

  • Dynamic Spectrum Access: Signal Processing, Networking, and Regulatory Policy

    Qing Zhao;Brian M. Sadler

  • Distributed Learning in Wireless Sensor Networks

    Ananthram Swami;Qing Zhao;Yao-Win Hong;Lang Tong

  • On Myopic Sensing for Multi-Channel Opportunistic Access

    Qing Zhao;Bhaskar Krishnamachari;Keqin Liu

Frequent Co-Authors

Ananthram Swami
Ananthram Swami United States Army Research Laboratory
Lang Tong
Lang Tong Cornell University
Bhaskar Krishnamachari
Bhaskar Krishnamachari University of Southern California
Chen-Nee Chuah
Chen-Nee Chuah University of California, Davis
Anna Scaglione
Anna Scaglione Cornell University
Amotz Bar-Noy
Amotz Bar-Noy City University of New York
Vikram Krishnamurthy
Vikram Krishnamurthy Cornell University
Tara Javidi
Tara Javidi University of California, San Diego
Mingyan Liu
Mingyan Liu University of Michigan–Ann Arbor
Saswati Sarkar
Saswati Sarkar University of Pennsylvania

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Finally, competency-based education offers an alternative route for students to demonstrate their skills and knowledge through practical assessments. Many institutions offer a list of competency-based colleges where you can earn degrees tailored to your pace and expertise, ideal for focused learners in engineering disciplines.

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