World's Best Scientists 2026 revealed!
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Fu Xiao

D-Index & Metrics

Engineering and Technology

D-Index
62
Citations
12080
World Ranking
1949
National Ranking
395

Fu Xiao 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 Fu Xiao 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+

This scientist: 154 publications — 29th percentile

29% of scientists in this discipline score the same or lower.

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

Fu Xiao 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 Fu Xiao 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+

This scientist: 62 D-Index — 81st percentile

81% of scientists in this discipline score the same or lower.

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

Overview

Fu Xiao is affiliated with the Hong Kong Polytechnic University in China and has made significant contributions in the field of engineering, particularly focusing on building energy and comfort optimization.

Their research covers a range of topics including:

  • Building Energy and Comfort Optimization
  • Smart Grid Energy Management
  • Energy Load and Power Forecasting
  • Energy Efficiency and Management
  • Refrigeration and Air Conditioning Technologies
  • Fire Detection and Safety Systems
  • Evacuation and Crowd Dynamics

The main fields of study addressed by Fu Xiao comprise engineering disciplines such as:

  • Building and Construction
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Renewable Energy, Sustainability and the Environment
  • Civil and Structural Engineering

Fu Xiao's frequent publication venues include:

  • Applied Energy
  • Building Simulation
  • Energy and Buildings
  • arXiv (Cornell University)
  • Journal of Building Engineering

Their common co-authors are:

  • Yanxue Li
  • Weijun Gao
  • Xinyan Huang
  • Zhe Chen
  • Chong Zhang

Selected recent papers illustrate the focus and scope of their work:

  • Interpretable machine learning for building energy management: A state-of-the-art review (2023), published in Advances in Applied Energy
  • Attention-based interpretable neural network for building cooling load prediction (2021), published in Applied Energy
  • Advanced data analytics for enhancing building performances: From data-driven to big data-driven approaches (2020), published in Building Simulation
  • Smart Detection of Fire Source in Tunnel Based on the Numerical Database and Artificial Intelligence (2020), published in Fire Technology
  • A real-time forecast of tunnel fire based on numerical database and artificial intelligence (2021), published in Building Simulation

Fu Xiao's research integrates advanced methodologies including interpretable machine learning and artificial intelligence to address challenges in energy management, load prediction, building performance, and fire safety systems.

Best Publications

  • A short-term building cooling load prediction method using deep learning algorithms

    Cheng Fan;Fu Xiao;Yang Zhao

  • Development of prediction models for next-day building energy consumption and peak power demand using data mining techniques

    Cheng Fan;Fu Xiao;Shengwei Wang

  • Quantitative energy performance assessment methods for existing buildings

    Shengwei Wang;Chengchu Yan;Fu Xiao

  • Peak load shifting control using different cold thermal energy storage facilities in commercial buildings: A review

    Yongjun Sun;Shengwei Wang;Fu Xiao;Diance Gao

  • AHU sensor fault diagnosis using principal component analysis method

    Shengwei Wang;Fu Xiao

  • Data mining in building automation system for improving building operational performance

    Fu Xiao;Cheng Fan

  • Pattern recognition-based chillers fault detection method using Support Vector Data Description (SVDD)

    Yang Zhao;Shengwei Wang;Fu Xiao

  • Research and application of evaporative cooling in China: A review (I) – Research

    Y.M. Xuan;Y.M. Xuan;F. Xiao;X.F. Niu;X.F. Niu;X. Huang

  • Analytical investigation of autoencoder-based methods for unsupervised anomaly detection in building energy data

    Cheng Fan;Fu Xiao;Yang Zhao;Jiayuan Wang

  • A framework for knowledge discovery in massive building automation data and its application in building diagnostics

    Cheng Fan;Fu Xiao;Chengchu Yan

  • An intelligent chiller fault detection and diagnosis methodology using Bayesian belief network

    Yang Zhao;Fu Xiao;Shengwei Wang

  • Unsupervised data analytics in mining big building operational data for energy efficiency enhancement: A review

    Cheng Fan;Fu Xiao;Zhengdao Li;Jiayuan Wang

  • Statistical investigations of transfer learning-based methodology for short-term building energy predictions

    Cheng Fan;Yongjun Sun;Fu Xiao;Jie Ma

  • An interactive building power demand management strategy for facilitating smart grid optimization

    Xue Xue;Shengwei Wang;Yongjun Sun;Fu Xiao

  • Attention-based interpretable neural network for building cooling load prediction

    Ao Li;Fu Xiao;Chong Zhang;Cheng Fan;Cheng Fan

  • Diagnostic Bayesian networks for diagnosing air handling units faults – part I: Faults in dampers, fans, filters and sensors

    Yang Zhao;Jin Wen;Fu Xiao;Xuebin Yang

  • A system-level fault detection and diagnosis strategy for HVAC systems involving sensor faults

    Shengwei Wang;Qiang Zhou;Fu Xiao

  • Advanced data analytics for enhancing building performances: From data-driven to big data-driven approaches

    Cheng Fan;Da Yan;Fu Xiao;Ao Li

  • A novel methodology to explain and evaluate data-driven building energy performance models based on interpretable machine learning

    Cheng Fan;Cheng Fan;Fu Xiao;Chengchu Yan;Chengliang Liu

  • Control performance of a dedicated outdoor air system adopting liquid desiccant dehumidification

    Fu Xiao;Gaoming Ge;Xiaofeng Niu

  • Temporal knowledge discovery in big BAS data for building energy management

    Cheng Fan;Fu Xiao;Henrik Madsen;Dan Wang

Frequent Co-Authors

Shengwei Wang
Shengwei Wang Hong Kong Polytechnic University
Xinhua Xu
Xinhua Xu Huazhong University of Science and Technology
Yongjun Sun
Yongjun Sun City University of Hong Kong
Yang Zhao
Yang Zhao Beijing Institute of Technology
Zhenjun Ma
Zhenjun Ma University of Wollongong
Gongsheng Huang
Gongsheng Huang City University of Hong Kong
Huanxin Chen
Huanxin Chen Huazhong University of Science and Technology
Li-Zhi Zhang
Li-Zhi Zhang South China University of Technology
Godfried Augenbroe
Godfried Augenbroe Georgia Institute of Technology
Mengjie Song
Mengjie Song Beijing Institute of Technology

External Links

Personal website of Fu Xiao Google Scholar page

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