World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
81
Citations
21440
World Ranking
504
National Ranking
171

Tianzhen Hong 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 Tianzhen Hong 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: 227 publications — 57th percentile

57% of scientists in this discipline score the same or lower.

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

Tianzhen Hong 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 Tianzhen Hong 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: 81 D-Index — 95th percentile

95% of scientists in this discipline score the same or lower.

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

Overview

Tianzhen Hong is affiliated with the Lawrence Berkeley National Laboratory in the United States. Their research primarily spans the fields of Engineering and Environmental Science, with a particular focus on Building and Construction, Environmental Engineering, and Electrical and Electronic Engineering. This multidisciplinary expertise also extends into Renewable Energy, Sustainability, and the Environment, as well as Speech and Hearing subfields.

The scientist's work covers a diverse range of topics related to energy systems and building environments. These topics include Building Energy and Comfort Optimization, Wind and Air Flow Studies, Urban Heat Island Mitigation, Smart Grid Energy Management, Noise Effects and Management, Energy Load and Power Forecasting, and Energy Efficiency and Management.

Frequent publication venues for Tianzhen Hong include:

  • Building and Environment
  • Energy and Buildings
  • Advances in Applied Energy
  • Applied Energy
  • Building Simulation

Co-authors collaborating regularly with Tianzhen Hong feature:

  • Han Li
  • Kaiyu Sun
  • Zhe Wang
  • Wanni Zhang
  • Jeetika Malik

Recent papers authored or co-authored by Tianzhen Hong highlight contributions to the understanding of climate impacts on energy systems, machine learning applications in building control, and energy flexibility. Notable works include:

  • "Quantifying the impacts of climate change and extreme climate events on energy systems," 2020, Nature Energy
  • "Reinforcement learning for building controls: The opportunities and challenges," 2020, Applied Energy
  • "Building thermal load prediction through shallow machine learning and deep learning," 2020, Applied Energy
  • "Energy flexibility of residential buildings: A systematic review of characterization and quantification methods and applications," 2021, Advances in Applied Energy
  • "State-of-the-art on research and applications of machine learning in the building life cycle," 2020, Energy and Buildings

Best Publications

  • Occupant behavior modeling for building performance simulation: Current state and future challenges:

    Da Yan;William O’Brien;Tianzhen Hong;Xiaohang Feng

  • Quantifying the impacts of climate change and extreme climate events on energy systems

    A. T.D. Perera;A. T.D. Perera;Vahid M. Nik;Vahid M. Nik;Vahid M. Nik;Deliang Chen;Jean Louis Scartezzini

  • Advances in research and applications of energy-related occupant behavior in buildings ☆

    Tianzhen Hong;Sarah C. Taylor-Lange;Simona D'Oca;Da Yan

  • Ten questions concerning occupant behavior in buildings: The big picture

    Tianzhen Hong;Da Yan;Simona D'Oca;Chien-fei Chen

  • Building simulation: an overview of developments and information sources

    Tianzhen Hong;S.K Chou;T.Y Bong

  • Ten questions on urban building energy modeling

    Tianzhen Hong;Yixing Chen;Yixing Chen;Xuan Luo;Na Luo

  • Reinforcement learning for building controls: The opportunities and challenges

    Zhe Wang;Tianzhen Hong

  • IEA EBC Annex 66: Definition and simulation of occupant behavior in buildings

    Da Yan;Tianzhen Hong;Bing Dong;Ardeshir Mahdavi

  • IEA EBC annex 53: Total energy use in buildings—Analysis and evaluation methods

    Hiroshi Yoshino;Tianzhen Hong;Natasa Nord

  • Building thermal load prediction through shallow machine learning and deep learning

    Zhe Wang;Tianzhen Hong;Mary Ann Piette

  • The human dimensions of energy use in buildings: A review

    Simona D’Oca;Tianzhen Hong;Jared Langevin

  • Automatic generation and simulation of urban building energy models based on city datasets for city-scale building retrofit analysis

    Yixing Chen;Tianzhen Hong;Mary Ann Piette

  • An ontology to represent energy-related occupant behavior in buildings. Part I: Introduction to the DNAs framework

    Tianzhen Hong;Simona D'Oca;Simona D'Oca;William J.N. Turner;William J.N. Turner;Sarah C. Taylor-Lange

  • Occupancy schedules learning process through a data mining framework

    Simona D’Oca;Tianzhen Hong

  • Energy flexibility of residential buildings: A systematic review of characterization and quantification methods and applications

    Han Li;Zhe Wang;Tianzhen Hong;Mary Ann Piette

  • State-of-the-art on research and applications of machine learning in the building life cycle

    Tianzhen Hong;Zhe Wang;Xuan Luo;Wanni Zhang

  • A data-mining approach to discover patterns of window opening and closing behavior in offices

    Simona D'Oca;Tianzhen Hong

  • Introducing IEA EBC annex 79: Key challenges and opportunities in the field of occupant-centric building design and operation

    William O'Brien;Andreas Wagner;Marcel Schweiker;Marcel Schweiker;Ardeshir Mahdavi

  • Simulation of occupancy in buildings

    Xiaohang Feng;Da Yan;Tianzhen Hong

  • Building simulation: Ten challenges

    Tianzhen Hong;Jared Langevin;Kaiyu Sun

  • A framework for quantifying the impact of occupant behavior on energy savings of energy conservation measures

    Kaiyu Sun;Tianzhen Hong

Frequent Co-Authors

Da Yan
Da Yan Tsinghua University
Mary Ann Piette
Mary Ann Piette Lawrence Berkeley National Laboratory
Xiaodong Xu
Xiaodong Xu University of Washington
Anna Laura Pisello
Anna Laura Pisello University of Perugia
William O'Brien
William O'Brien Carleton University
Bing Dong
Bing Dong Syracuse University
Borong Lin
Borong Lin Tsinghua University
Siaw Kiang Chou
Siaw Kiang Chou National University of Singapore
Michael Wetter
Michael Wetter Lawrence Berkeley National Laboratory
Costas J. Spanos
Costas J. Spanos University of California, Berkeley

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