World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
48
Citations
10844
World Ranking
4504
National Ranking
1293

T. Warren Liao 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 T. Warren Liao 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: 171 publications — 36th percentile

36% of scientists in this discipline score the same or lower.

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

T. Warren Liao 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 T. Warren Liao 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: 48 D-Index — 55th percentile

55% of scientists in this discipline score the same or lower.

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

Overview

T. Warren Liao is affiliated with Louisiana State University in the United States. Their research primarily spans the field of Engineering with a particular focus on Industrial and Manufacturing Engineering, Mechanical Engineering, Computer Vision and Pattern Recognition, Management Science and Operations Research, as well as Statistics, Probability and Uncertainty.

The main topics addressed in their work include:

  • Advanced Manufacturing and Logistics Optimization
  • Advanced Machining Processes and Optimization
  • Scheduling and Optimization Algorithms
  • Assembly Line Balancing Optimization
  • Optimization and Packing Problems
  • Multi-Criteria Decision Making
  • Digital Transformation in Industry

Liao's recent publications demonstrate engagement with optimization algorithms and manufacturing processes, highlighting developments in materials design and predictive modeling. Selected recent papers include:

  • Metaheuristic-based inverse design of materials - A survey (2020), Journal of Materiomics
  • Developing a Reliability Model of CNC System under Limited Sample Data Based on Multisource Information Fusion (2020), Mathematical Problems in Engineering
  • Multitask Scheduling in Consideration of Fuzzy Uncertainty of Multiple Criteria in Service-Oriented Manufacturing (2020), IEEE Transactions on Fuzzy Systems
  • Prediction using multi-objective slime mould algorithm optimized support vector regression model (2023), Applied Soft Computing
  • Improving milling tool wear prediction through a hybrid NCA-SMA-GRU deep learning model (2024), Expert Systems with Applications

The venues where Liao has published more than once reveal consistent contributions to both established and emerging outlets. These venues include:

  • arXiv (Cornell University)
  • Systems and Soft Computing
  • Advanced Engineering Informatics
  • IEEE Transactions on Intelligent Transportation Systems
  • The International Journal of Advanced Manufacturing Technology

Throughout their career, Liao has collaborated frequently with researchers such as Chong Peng, Hongyi Zhou, Yuzhen Cai, Zhongyuan Che, and Zhongwen Zhang. These collaborations appear in a range of publications focusing on manufacturing systems, material design, and scheduling algorithms.

Best Publications

  • Clustering of time series data-a survey

    T. Warren Liao

  • Automatic identification of different types of welding defects in radiographic images

    Gang Wang;T.Warren Liao

  • SIMILARITY MEASURES FOR RETRIEVAL IN CASE-BASED REASONING SYSTEMS

    T. Warren Liao;Zhiming Zhang;Claude R. Mount

  • Two hybrid differential evolution algorithms for engineering design optimization

    T. Warren Liao

  • A new age-based replenishment policy for supply chain inventory optimization of highly perishable products

    Qinglin Duan;T. Warren Liao

  • CLPS-GA: A case library and Pareto solution-based hybrid genetic algorithm for energy-aware cloud service scheduling

    Fei Tao;Ying Feng;Lin Zhang;T.W. Liao

  • Surface/subsurface damage and the fracture strength of ground ceramics

    Kun Li;T Warren Liao

  • Optimization of blood supply chain with shortened shelf lives and ABO compatibility

    Qinglin Duan;T. Warren Liao

  • An automated radiographic NDT system for weld inspection: Part II—Flaw detection

    T.Warren Liao;Yueming Li

  • Medical data mining by fuzzy modeling with selected features

    Unknown

  • Metaheuristics for project and construction management – A state-of-the-art review

    T. Warren Liao;P.J. Egbelu;B.R. Sarker;S.S. Leu

  • Prediction of tensile strength of friction stir weld joints with adaptive neuro-fuzzy inference system (ANFIS) and neural network

    Mohammad W. Dewan;Daniel J. Huggett;T. Warren Liao;Muhammad A. Wahab

  • A wavelet-based methodology for grinding wheel condition monitoring

    T. Warren Liao;Chi-Fen Ting;J. Qu;P.J. Blau

  • Simultaneous dock assignment and sequencing of inbound trucks under a fixed outbound truck schedule in multi-door cross docking operations

    T.W. Liao;P.J. Egbelu;P.C. Chang

  • A fuzzy multicriteria decision-making method for material selection

    T.Warren Liao

  • Combining SOM and fuzzy rule base for flow time prediction in semiconductor manufacturing factory

    P. C. Chang;T. W. Liao

  • An automated radiographic NDT system for weld inspection: Part I — Weld extraction

    T.Warren Liao;Jiawei Ni

  • Feature extraction and selection from acoustic emission signals with an application in grinding wheel condition monitoring

    T. Warren Liao

  • A neural network approach for grinding processes: Modelling and optimization

    T. Warren Liao;L.J. Chen

  • Classification of welding flaw types with fuzzy expert systems

    Unknown

  • Evolving fuzzy rules for due-date assignment problem in semiconductor manufacturing factory

    Pei-Chann Chang;Jih-Chang Hieh;T. Warren Liao

  • BGM-BLA: A New Algorithm for Dynamic Migration of Virtual Machines in Cloud Computing

    Fei Tao;Chen Li;T. Warren Liao;Yuanjun Laili

  • Two hybrid differential evolution algorithms for optimal inbound and outbound truck sequencing in cross docking operations

    T. W. Liao;P. J. Egbelu;P. C. Chang

Frequent Co-Authors

Pei-Chann Chang
Pei-Chann Chang Yuan Ze University
Peter J. Blau
Peter J. Blau Oak Ridge National Laboratory
Jun Qu
Jun Qu Oak Ridge National Laboratory
Fei Tao
Fei Tao Beihang University
Bhaba R. Sarker
Bhaba R. Sarker Louisiana State University
Guoqiang Li
Guoqiang Li Louisiana State University
Wentong Cai
Wentong Cai Nanyang Technological University
Lin Zhang
Lin Zhang Beihang University

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