World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
45
Citations
7307
World Ranking
7271
National Ranking
3172

Miao Pan publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Miao Pan sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 266 publications — 66th percentile

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

The last bar groups every scientist with 991 publications or more.

Miao Pan D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Miao Pan sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 45 D-Index — 51st percentile

51% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Miao Pan is affiliated with the University of Houston in the United States and has an extensive publication record in the fields of Engineering and Computer Science, with a focus on Electrical and Electronic Engineering, Artificial Intelligence, and Computer Networks and Communications. Their research spans several interdisciplinary subfields including Aerospace Engineering and Computational Mechanics.

The scientist's recent work includes contributions on various topics related to privacy-preserving technologies, localization, and network optimization. Notable recent papers are:

  • "Federated Learning in Vehicular Edge Computing: A Selective Model Aggregation Approach," 2020, IEEE Access
  • "Incentivizing Differentially Private Federated Learning: A Multidimensional Contract Approach," 2021, IEEE Internet of Things Journal
  • "Task-Oriented Intelligent Networking Architecture for the Space-Air-Ground-Aqua Integrated Network," 2020, IEEE Internet of Things Journal
  • "IoT Device Friendly and Communication-Efficient Federated Learning via Joint Model Pruning and Quantization," 2022, IEEE Internet of Things Journal
  • "Privacy Preserving Participant Recruitment for Coverage Maximization in Location Aware Mobile Crowdsensing," 2021, IEEE Transactions on Mobile Computing

Key areas of research focus for Miao Pan include:

  • Privacy-Preserving Technologies in Data
  • Indoor and Outdoor Localization Technologies
  • UAV Applications and Optimization
  • Mineral Processing and Grinding
  • IoT and Edge/Fog Computing
  • Granular Flow and Fluidized Beds
  • Advanced MIMO Systems Optimization

Miao Pan frequently publishes in several noted scientific venues. The prominent publication outlets include:

  • arXiv (Cornell University)
  • IEEE Internet of Things Journal
  • IEEE Transactions on Vehicular Technology
  • IEEE Transactions on Mobile Computing
  • Powder Technology

The scientist collaborates regularly with a group of co-authors, showing active involvement in joint research activities. Frequent co-authors include Haishen Jiang, Zhu Han, Chenlong Duan, Jie Wang, and Jiahao Ding.

Best Publications

  • Federated Learning in Vehicular Edge Computing: A Selective Model Aggregation Approach

    Dongdong Ye;Rong Yu;Miao Pan;Zhu Han

  • Optimal Power Management of Residential Customers in the Smart Grid

    Yuanxiong Guo;Miao Pan;Yuguang Fang

  • Optimal VNF Placement via Deep Reinforcement Learning in SDN/NFV-Enabled Networks

    Jianing Pei;Peilin Hong;Miao Pan;Jiangqing Liu

  • Decentralized Coordination of Energy Utilization for Residential Households in the Smart Grid

    Yuanxiong Guo;Miao Pan;Yuguang Fang;Pramod P. Khargonekar

  • IoT Enabled UAV: Network Architecture and Routing Algorithm

    Qixun Zhang;Menglei Jiang;Zhiyong Feng;Wei Li

  • Traffic-aware multiple mix zone placement for protecting location privacy

    Xinxin Liu;Han Zhao;Miao Pan;Hao Yue

  • To Talk or to Work: Flexible Communication Compression for Energy Efficient Federated Learning over Heterogeneous Mobile Edge Devices

    Liang Li;Dian Shi;Ronghui Hou;Hui Li

  • Joint Radio and Computational Resource Allocation in IoT Fog Computing

    Yunan Gu;Zheng Chang;Miao Pan;Lingyang Song

  • Secure Communications in NOMA System: Subcarrier Assignment and Power Allocation

    Haijun Zhang;Ning Yang;Keping Long;Miao Pan

  • Incentivizing Differentially Private Federated Learning: A Multidimensional Contract Approach

    Maoqiang Wu;Dongdong Ye;Jiahao Ding;Yuanxiong Guo

  • Maximum Lifetime Scheduling for Target Coverage and Data Collection in Wireless Sensor Networks

    Zaixin Lu;Wei Wayne Li;Miao Pan

  • Matching and Cheating in Device to Device Communications Underlying Cellular Networks

    Yunan Gu;Yanru Zhang;Miao Pan;Zhu Han

  • Joint routing and link scheduling for cognitive radio networks under uncertain spectrum supply

    Miao Pan;Chi Zhang;Pan Li;Yuguang Fang

  • A Survey of Contract Theory-Based Incentive Mechanism Design in Wireless Networks

    Yanru Zhang;Miao Pan;Lingyang Song;Zaher Dawy

  • Cooperative Communication Aware Link Scheduling for Cognitive Vehicular Networks

    Miao Pan;Pan Li;Yuguang Fang

  • Purging the Back-Room Dealing: Secure Spectrum Auction Leveraging Paillier Cryptosystem

    Miao Pan;Jinyuan Sun;Yuguang Fang

  • Toward Accurate Device-Free Wireless Localization With a Saddle Surface Model

    Jie Wang;Qinghua Gao;Miao Pan;Xiao Zhang

  • A time-efficient information collection protocol for large-scale RFID systems

    Hao Yue;Chi Zhang;Miao Pan;Yuguang Fang

  • Task-Oriented Intelligent Networking Architecture for the Space–Air–Ground–Aqua Integrated Network

    Jun Liu;Xinqi Du;Junhong Cui;Miao Pan

  • Incentive Mechanism for Mobile Crowdsourcing Using an Optimized Tournament Model

    Yanru Zhang;Chunxiao Jiang;Lingyang Song;Miao Pan

  • Optimal Resource Rental Planning for Elastic Applications in Cloud Market

    Han Zhao;Miao Pan;Xinxin Liu;Xiaolin Li

  • Noncoherent Backscatter Communications Over Ambient OFDM Signals

    Mohamed A. ElMossallamy;Miao Pan;Riku Jantti;Karim G. Seddik

  • Efficient data collection for wireless rechargeable sensor clusters in Harsh terrains using UAVs

    Yawei Pang;Yanru Zhang;Yunan Gu;Miao Pan

  • Device-Free Wireless Sensing: Challenges, Opportunities, and Applications

    Jie Wang;Qinhua Gao;Miao Pan;Yuguang Fang

Frequent Co-Authors

Zhu Han
Zhu Han University of Houston
Yuguang Fang
Yuguang Fang City University of Hong Kong
Pan Li
Pan Li Case Western Reserve University
Chi Zhang
Chi Zhang University of Science and Technology of China
Rong Yu
Rong Yu Guangdong University of Technology
Lingyang Song
Lingyang Song Peking University
Riku Jantti
Riku Jantti Aalto University
Ping Zhang
Ping Zhang Beijing University of Posts and Telecommunications
Zaher Dawy
Zaher Dawy American University of Beirut
Haijun Zhang
Haijun Zhang University of Science and Technology Beijing

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

Choosing the right educational pathway in Computer Science can be a critical decision, especially with the growing number of online options. Many students seek flexibility and affordability. For those considering a head start or a more accessible entry point, associates degrees online offer a foundation in Computer Science and IT, perfect for career changers or new learners.

Advancing your career often requires further specialization. If you want to accelerate your studies, there are quick masters degrees online that allow qualified students to complete a master’s in as little as one year. This can boost your credentials and help fast-track your career.

For those wondering about the job market, it's important to consider which master's degree is most in demand in usa. Tech-focused master's degrees, especially in fields like data science, cybersecurity, and artificial intelligence, are highly valued by employers nationwide.

Affordability remains a top concern. Many reputable institutions now provide cheap online college classes, making it easier to pursue your education without incurring significant debt. With the right online degree, you can tailor your learning to meet both your budget and your career goals.

Best Scientists Citing Miao Pan

Trending Scientists

Recently Published Articles