World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
47
Citations
7521
World Ranking
4936
National Ranking
201

Liping Fu 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 Liping Fu 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: 208 publications — 51st percentile

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

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

Liping Fu 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 Liping Fu 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: 47 D-Index — 52nd percentile

52% of scientists in this discipline score the same or lower.

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

Overview

Liping Fu is affiliated with the University of Waterloo in Canada and specializes in engineering, with substantial contributions in several subfields including building and construction, transportation, safety, risk, reliability and quality, civil and structural engineering, and control and systems engineering.

Their research extensively covers topics such as traffic prediction and management techniques, traffic control and management, traffic and road safety, transportation planning and optimization, autonomous vehicle technology and safety, infrastructure maintenance and monitoring, and railway systems and energy efficiency.

Recent publications authored or co-authored by Liping Fu include the following:

  • A proactive lane-changing risk prediction framework considering driving intention recognition and different lane-changing patterns, 2021, Accident Analysis & Prevention
  • Modeling train operation as sequences: A study of delay prediction with operation and weather data, 2020, Transportation Research Part E Logistics and Transportation Review
  • A Bayesian network model to predict the effects of interruptions on train operations, 2020, Transportation Research Part C Emerging Technologies
  • Inverse Modeling for Filters Using a Regularized Deep Neural Network Approach, 2020, IEEE Microwave and Wireless Components Letters
  • Modeling train timetables as images: A cost-sensitive deep learning framework for delay propagation pattern recognition, 2021, Expert Systems with Applications

Frequent collaborators in their research include Guangyuan Pan, Chao Wen, Ping Huang, Chaozhe Jiang, and Ting Fu.

Publications by Liping Fu appear regularly in several venues, notably:

  • arXiv (Cornell University)
  • Canadian Journal of Civil Engineering
  • Accident Analysis & Prevention
  • Transportation Research Part C Emerging Technologies
  • Expert Systems with Applications

Best Publications

  • Heuristic shortest path algorithms for transportation applications: state of the art

    L. Fu;D. Sun;L. R. Rilett

  • Expected shortest paths in dynamic and stochastic traffic networks

    Liping Fu;L.R. Rilett

  • Real-Time Optimization Model for Dynamic Scheduling of Transit Operations

    Liping Fu;Qing Liu;Paul Calamai

  • A latent class modeling approach for identifying vehicle driver injury severity factors at highway-railway crossings.

    Naveen Eluru;Morteza Bagheri;Luis F. Miranda-Moreno;Liping Fu

  • An adaptive routing algorithm for in-vehicle route guidance systems with real-time information

    Liping Fu

  • Quantifying safety benefit of winter road maintenance: Accident frequency modeling

    Taimur Usman;Liping Fu;Luis F. Miranda-Moreno

  • Identification of crash hotspots using kernel density estimation and kriging methods: a comparison

    Lalita Thakali;Tae J. Kwon;Liping Fu;Liping Fu

  • Design and Implementation of Bus-Holding Control Strategies with Real-Time Information

    Liping Fu;Xuhui Yang

  • Scheduling dial-a-ride paratransit under time-varying, stochastic congestion

    Liping Fu

  • Reducing bias in probe-based arterial link travel time estimates

    Bruce R. Hellinga;Liping Fu

  • Predicting Bus Arrival Time on the Basis of Global Positioning System Data

    Dihua Sun;Hong Luo;Liping Fu;Weining Liu

  • Decomposing Travel Times Measured by Probe-based Traffic Monitoring Systems to Individual Road Segments

    Bruce R Hellinga;Pedram Izadpanah;Hiroyuki Takada;Liping Fu

  • Alternative Risk Models for Ranking Locations for Safety Improvement

    Luis F. Miranda-Moreno;LP Fu;Fedel Frank Saccomanno;Aurelie Labbe

  • A simulation model for evaluating advanced dial-a-ride paratransit systems

    Liping Fu

  • An automatic image recognition system for winter road surface condition classification

    Raqib Omer;Liping Fu

  • A deep learning approach for multi-attribute data: A study of train delay prediction in railway systems

    Ping Huang;Ping Huang;Chao Wen;Chao Wen;Liping Fu;Qiyuan Peng

  • A hybrid Bayesian network model for predicting delays in train operations

    Javad Lessan;Liping Fu;Liping Fu;Chao Wen;Chao Wen

  • A New Performance Index for Evaluating Transit Quality of Service

    Liping Fu;Yaping Xin

  • Assessing Expected Accuracy of Probe Vehicle Travel Time Reports

    Bruce Hellinga;Liping Fu

  • Delay Variability at Signalized Intersections

    Liping Fu;Bruce Hellinga

  • A disaggregate model for quantifying the safety effects of winter road maintenance activities at an operational level.

    Taimur Usman;Liping Fu;Luis F. Miranda-Moreno

Frequent Co-Authors

Luis F Miranda-Moreno
Luis F Miranda-Moreno McGill University
Dominique Lord
Dominique Lord Texas A&M University
Laurence R. Rilett
Laurence R. Rilett Auburn University
Ming Yu
Ming Yu Chinese University of Hong Kong
Bani K. Mallick
Bani K. Mallick Texas A&M University
Naveen Eluru
Naveen Eluru University of Central Florida
Lawrence Joseph
Lawrence Joseph McGill University
Satish V. Ukkusuri
Satish V. Ukkusuri Purdue University West Lafayette
Ashkan Rahimi-Kian
Ashkan Rahimi-Kian University of Tehran

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