World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
71
Citations
16435
World Ranking
1807
National Ranking
251

Xiaohong Guan 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 Xiaohong Guan 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: 517 publications — 94th percentile

94% of scientists in this discipline score the same or lower.

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

Xiaohong Guan 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 Xiaohong Guan 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: 71 D-Index — 88th percentile

88% of scientists in this discipline score the same or lower.

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

Overview

Xiaohong Guan is affiliated with Xi'an Jiaotong University in China and has contributed extensively to the engineering and computer science fields, particularly focusing on electrical and electronic engineering, artificial intelligence, and control and systems engineering.

Their recent publications span several key areas related to smart grid technologies, energy management, and intelligent control systems. Representative works include:

  • A Review of Deep Reinforcement Learning for Smart Building Energy Management (2021, IEEE Internet of Things Journal)
  • Multi-Agent Deep Reinforcement Learning for HVAC Control in Commercial Buildings (2020, IEEE Transactions on Smart Grid)
  • Optimal planning of distributed hydrogen-based multi-energy systems (2020, Applied Energy)
  • Distributed Observer-Based Event-Triggered Load Frequency Control of Multiarea Power Systems Under Cyber Attacks (2022, IEEE Transactions on Automation Science and Engineering)
  • Wireless Covert Communications Aided by Distributed Cooperative Jamming Over Slow Fading Channels (2021, IEEE Transactions on Wireless Communications)

The primary topics of research explored by Guan include:

  • Smart Grid Energy Management
  • Microgrid Control and Optimization
  • Optimal Power Flow Distribution
  • Smart Grid Security and Resilience
  • Electric Vehicles and Infrastructure
  • Electric Power System Optimization
  • Advanced Graph Neural Networks

Guan has collaborated frequently with several co-authors over the years. These include Zhanbo Xu, Qiaozhu Zhai, Pinghui Wang, Jiang Wu, and Junzhou Zhao, reflecting a consistent network of research partnerships.

The venues where Guan most often publishes research demonstrate a focus on engineering, automation, and smart grid technologies. These venues include:

  • arXiv (Cornell University)
  • IEEE Transactions on Automation Science and Engineering
  • IEEE Transactions on Smart Grid
  • IEEE Transactions on Knowledge and Data Engineering
  • SSRN Electronic Journal

In addition to journal papers, Guan has contributed books through Springer Science+Business Media, including titles such as Information and Communications Security (2021) and Music Intelligence (2024).

The combination of topics, co-authorship, and publication venues indicates a research profile centered on the intersection of engineering methodologies and computer science applications, targeting issues in energy systems, intelligent control, and secure communication within smart grids and other distributed infrastructure systems.

Best Publications

  • Energy-Efficient Buildings Facilitated by Microgrid

    Xiaohong Guan;Zhanbo Xu;Qing-Shan Jia

  • A Review of Deep Reinforcement Learning for Smart Building Energy Management

    Liang Yu;Shuqi Qin;Meng Zhang;Chao Shen

  • An optimization-based method for unit commitment

    X. Guan;P.B. Luh;H. Yan;J.A. Amalfi

  • Multi-Agent Deep Reinforcement Learning for HVAC Control in Commercial Buildings

    Liang Yu;Yi Sun;Zhanbo Xu;Chao Shen

  • An SVM-based machine learning method for accurate internet traffic classification

    Ruixi Yuan;Zhu Li;Xiaohong Guan;Li Xu

  • Coordinated Multi-Microgrids Optimal Control Algorithm for Smart Distribution Management System

    Jiang Wu;Xiaohong Guan

  • Performance Analysis and Comparison on Energy Storage Devices for Smart Building Energy Management

    Zhanbo Xu;Xiaohong Guan;Qing-Shan Jia;Jiang Wu

  • Nonlinear approximation method in Lagrangian relaxation-based algorithms for hydrothermal scheduling

    Xiaohong Guan;P.B. Luh;Lan Zhang

  • Fast Identification of Inactive Security Constraints in SCUC Problems

    Qiaozhu Zhai;Xiaohong Guan;Jinghui Cheng;Hongyu Wu

  • User Authentication Through Mouse Dynamics

    Chao Shen;Zhongmin Cai;Xiaohong Guan;Youtian Du

  • Optimization based methods for unit commitment: Lagrangian relaxation versus general mixed integer programming

    Xiaohong Guan;Qiaozhu Zhai;A. Papalexopoulos

  • Performance Analysis of Multi-Motion Sensor Behavior for Active Smartphone Authentication

    Chao Shen;Yuanxun Li;Yufei Chen;Xiaohong Guan

  • Forecasting power market clearing price and quantity using a neural network method

    Feng Gao;Xiaohong Guan;Xi-Ren Cao;A. Papalexopoulos

  • Optimization-based scheduling of hydrothermal power systems with pumped-storage units

    Xiaohong Guan;P.B. Luh;Houzhong Yen;P. Rogan

  • Revenue adequate bidding strategies in competitive electricity markets

    Chao-An Li;A.J. Svoboda;Xiaohong Guan;H. Singh

  • Integrated Energy Exchange Scheduling for Multimicrogrid System With Electric Vehicles

    Dai Wang;Xiaohong Guan;Jiang Wu;Pan Li

  • Unit commitment with identical units successive subproblem solving method based on Lagrangian relaxation

    Qiaozhu Zhai;Xiaohong Guan;Jian Cui

  • Purchase allocation and demand bidding in electric power markets

    X. Guan;L. Yaan

  • Matching EV Charging Load With Uncertain Wind: A Simulation-Based Policy Improvement Approach

    Qilong Huang;Qing-Shan Jia;Zhifeng Qiu;Xiaohong Guan

  • Scheduling hydrothermal power systems with cascaded and head-dependent reservoirs

    Ernan Xi;Xiaohong Guan;Renhou Li

  • Accurate Classification of the Internet Traffic Based on the SVM Method

    Zhu Li;Ruixi Yuan;Xiaohong Guan

  • Energy efficient buildings facilitated by micro grid

    Xiaohong Guan;Zhanbo Xu;Qingshan Jia

Frequent Co-Authors

Qing-Shan Jia
Qing-Shan Jia Tsinghua University
Don Towsley
Don Towsley University of Massachusetts Amherst
John C. S. Lui
John C. S. Lui Chinese University of Hong Kong
Qinghua Zheng
Qinghua Zheng Xi'an Jiaotong University
Qianchuan Zhao
Qianchuan Zhao Tsinghua University
Xiangliang Zhang
Xiangliang Zhang University of Notre Dame
Peter B. Luh
Peter B. Luh University of Connecticut
Wei Wang
Wei Wang Beijing Jiaotong University
Zhenguo Li
Zhenguo Li Huawei Technologies (China)
Lang Tong
Lang Tong Cornell University

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