World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
32
Citations
3281
World Ranking
9611
National Ranking
1583

Yuan Gao 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 Yuan Gao sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 134 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: 117 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: 59 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: 68 publications — 2nd percentile

2% of scientists in this discipline score the same or lower.

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

Yuan Gao 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 Yuan Gao sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 128 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: 349 scientists 41 D-Index: 362 scientists 42 D-Index: 425 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: 94 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: 24 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: 32 D-Index — 3rd percentile

3% of scientists in this discipline score the same or lower.

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

Overview

Yuan Gao is affiliated with the Beijing Institute of Technology in China, contributing extensively to the field of engineering with a focus on railway systems and transportation optimization. Their research spans multiple subfields within engineering, including industrial and manufacturing engineering, electrical and electronic engineering, transportation, mechanical engineering, and control and systems engineering.

Their work has concentrated on a variety of main topics:

  • Railway Systems and Energy Efficiency
  • Transportation Planning and Optimization
  • Railway Engineering and Dynamics
  • Maritime Ports and Logistics
  • Vehicle Routing Optimization Methods
  • Microgrid Control and Optimization
  • Smart Grid Energy Management

Yuan Gao has published research in several frequently appearing venues, with multiple articles in prominent journals and conferences:

  • Transportation Research Part B Methodological
  • E3S Web of Conferences
  • IOP Conference Series Earth and Environmental Science
  • European Journal of Operational Research
  • Omega

Recent publications by Yuan Gao include:

  • Joint optimization of train scheduling and maintenance planning in a railway network: A heuristic algorithm using Lagrangian relaxation, 2020, Transportation Research Part B Methodological
  • Integrated optimization of train timetable, rolling stock assignment and short-turning strategy for a metro line, 2021, European Journal of Operational Research
  • Joint optimization of train timetabling and rolling stock circulation planning: A novel flexible train composition mode, 2022, Transportation Research Part B Methodological
  • Integrated optimization of line planning and train timetabling in railway corridors with passengers' expected departure time interval, 2021, Computers & Industrial Engineering
  • Train rescheduling for large-scale disruptions in a large-scale railway network, 2023, Transportation Research Part B Methodological

The scientist has collaborated frequently with a number of co-authors, including:

  • Lixing Yang
  • Dunnan Liu
  • Chuntian Zhang
  • Ziyou Gao
  • Jianguo Qi

The body of work produced by Yuan Gao covers complex optimization problems related to railway networks and transportation systems, integrating multiple aspects such as train scheduling, maintenance planning, rolling stock circulation, and timetabling under varying operational constraints. Their interdisciplinary approach incorporates elements from control engineering and logistics to address efficiency and dynamics in railway and transportation infrastructure.

Best Publications

  • Shortest path problem with uncertain arc lengths

    Yuan Gao

  • Some stability theorems of uncertain differential equation

    Kai Yao;Jinwu Gao;Yuan Gao

  • Rescheduling a metro line in an over-crowded situation after disruptions

    Yuan Gao;Leo Kroon;Marie Schmidt;Lixing Yang

  • Collaborative optimization for train scheduling and train stop planning on high-speed railways

    Lixing Yang;Jianguo Qi;Shukai Li;Yuan Gao

  • CU Partition Mode Decision for HEVC Hardwired Intra Encoder Using Convolution Neural Network

    Zhenyu Liu;Xianyu Yu;Yuan Gao;Shaolin Chen

  • Uncertain models for single facility location problems on networks

    Yuan Gao

  • ON LIU'S INFERENCE RULE FOR UNCERTAIN SYSTEMS

    Xin Gao;Yuan Gao;Dan A. Ralescu

  • Fault tree analysis combined with quantitative analysis for high-speed railway accidents

    Pei Liu;Lixing Yang;Ziyou Gao;Shukai Li

  • Joint optimization of train scheduling and maintenance planning in a railway network: A heuristic algorithm using Lagrangian relaxation

    Chuntian Zhang;Yuan Gao;Lixing Yang;Ziyou Gao

  • CONNECTEDNESS INDEX OF UNCERTAIN GRAPH

    Xiulian Gao;Yuan Gao

  • Reduction methods of type-2 uncertain variables and their applications to solid transportation problem

    Lixing Yang;Pei Liu;Shukai Li;Yuan Gao

  • Integrated optimization of train timetable, rolling stock assignment and short-turning strategy for a metro line

    Jiawei Yuan;Yuan Gao;Shukai Li;Pei Liu

  • On distribution function of the diameter in uncertain graph

    Yuan Gao;Lixing Yang;Shukai Li;Samarjit Kar

  • Uncertain inference control for balancing an inverted pendulum

    Yuan Gao

  • Energy-Efficient Train Timetable Optimization in the Subway System with Energy Storage Devices

    Pei Liu;Lixing Yang;Ziyou Gao;Yeran Huang

  • Three-stage optimization method for the problem of scheduling additional trains on a high-speed rail corridor

    Yuan Gao;Leo Kroon;Lixing Yang;Ziyou Gao

  • Integrated optimization for train operation zone and stop plan with passenger distributions

    Jianguo Qi;Lixing Yang;Zhen Di;Zhen Di;Shukai Li

  • A chance constrained programming approach for uncertain p-hub center location problem

    Yuan Gao;Zhongfeng Qin

  • Energy consumption and travel time analysis for metro lines with express/local mode

    Yuan Gao;Lixing Yang;Ziyou Gao

  • Integrated optimization of train scheduling and maintenance planning on high-speed railway corridors

    Chuntian Zhang;Yuan Gao;Lixing Yang;Uday Kumar

  • Uncertain models on railway transportation planning problem

    Yuan Gao;Lixing Yang;Shukai Li

Frequent Co-Authors

Lixing Yang
Lixing Yang Beijing Jiaotong University
Dan A. Ralescu
Dan A. Ralescu University of Cincinnati
Leo Kroon
Leo Kroon Erasmus University Rotterdam
Samarjit Kar
Samarjit Kar National Institute of Technology Durgapur
Uday Kumar
Uday Kumar Luleå University of Technology

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