World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
37
Citations
7674
World Ranking
8278
National Ranking
525

David M. Lane 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 David M. Lane 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: 244 publications — 63rd percentile

63% of scientists in this discipline score the same or lower.

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

David M. Lane 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 David M. Lane 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: 37 D-Index — 16th percentile

16% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2010 - Fellow of the Royal Society of Edinburgh

Overview

David M. Lane is affiliated with Heriot-Watt University in the United Kingdom. Their research spans multiple fields, primarily Medicine and Engineering, with a focus on subfields such as Psychiatry and Mental Health, Cognitive Neuroscience, Small Animals, Sociology and Political Science, and Artificial Intelligence.

The main topics in their body of work include Attention Deficit Hyperactivity Disorder, Autism Spectrum Disorder Research, Child Nutrition and Feeding Issues, Veterinary Orthopedics and Neurology, Underwater Vehicles and Communication Systems, Robot Manipulation and Learning, and Reinforcement Learning in Robotics.

Recent scientific papers by David M. Lane cover a range of interdisciplinary subjects:

  • "Learning Mobile Manipulation through Deep Reinforcement Learning" (2020), published in Sensors
  • "ADHD severity as a predictor of cognitive task performance in children with Autism Spectrum Disorder (ASD)" (2021), published in Research in Developmental Disabilities
  • "Training Users to Identify Phishing Emails" (2021), published in Journal of Educational Computing Research
  • "Executive Function in Autism: Association with ADHD and ASD Symptoms" (2021), published in Journal of Autism and Developmental Disorders
  • "Effects of Extended-Release Methylphenidate Treatment on Cognitive Task Performance in Children with Autism Spectrum Disorder and Attention-Deficit/Hyperactivity Disorder" (2020), published in Journal of Child and Adolescent Psychopharmacology

David M. Lane has collaborated frequently with a group of coauthors, including:

  • Rosleen Mansour
  • Anthony R. Ward
  • Katherine A. Loveland
  • Michael G. Aman
  • Deborah A. Pearson

Their publications are distributed across specialized journals such as Sensors, Research in Developmental Disabilities, Journal of Educational Computing Research, Journal of Autism and Developmental Disorders, and Journal of Child and Adolescent Psychopharmacology.

In recognition of their professional contributions, David M. Lane was awarded the title of Fellow of the Royal Society of Edinburgh in 2010.

Best Publications

  • Review of fish swimming modes for aquatic locomotion

    M. Sfakiotakis;D.M. Lane;J.B.C. Davies

  • Path Planning for Autonomous Underwater Vehicles

    C. Petres;Y. Pailhas;P. Patron;Y. Petillot

  • Underwater vehicle obstacle avoidance and path planning using a multi-beam forward looking sonar

    Y. Petillot;I. Tena Ruiz;D.M. Lane

  • Autonomous docking for Intervention-AUVs using sonar and video-based real-time 3D pose estimation

    J. Evans;P. Redmond;C. Plakas;K. Hamilton

  • Concurrent mapping and localization using sidescan sonar

    I. Tena Ruiz;S. de Raucourt;Y. Petillot;D.M. Lane

  • AMADEUS: advanced manipulation for deep underwater sampling

    D.M. Lane;J.B.C. Davies;G. Casalino;G. Bartolini

  • The AMADEUS dextrous subsea hand: design, modeling, and sensor processing

    D.M. Lane;J.B.C. Davies;G. Robinson;D.J. O'Brien

  • Multiresolution 3-D Reconstruction From Side-Scan Sonar Images

    E. Coiras;Y. Petillot;D.M. Lane

  • Robust tracking of multiple objects in sector-scan sonar image sequences using optical flow motion estimation

    D.M. Lane;M.J. Chantler;Dongyong Dai

  • Underwater path planing using fast marching algorithms

    C. Petres;Y. Pailhas;Y. Petillot;D. Lane

  • Bio-inspired wideband sonar signals based on observations of the bottlenose dolphin (Tursiops truncatus).

    Christopher Capus;Yan Pailhas;Keith Brown;David Michael Lane

  • Semantic Knowledge-Based Framework to Improve the Situation Awareness of Autonomous Underwater Vehicles

    Emilio Miguelañez;Pedro Patrón;Keith E Brown;Yvan R Petillot

  • Learning Mobile Manipulation through Deep Reinforcement Learning.

    Cong Wang;Qifeng Zhang;Qiyan Tian;Shuo Li

  • Texture analysis for seabed classification: co-occurrence matrices vs. self-organizing maps

    N. Pican;E. Trucco;M. Ross;D.M. Lane

  • Hybrid position/force control of a hydraulic underwater manipulator

    M.W. Dunnigan;D.M. Lane;A.C. Clegg;I. Edwards

  • The ARROWS project: adapting and developing robotics technologies for underwater archaeology

    Benedetto Allotta;Riccardo Costanzi;Alessandro Ridolfi;Carlo Colombo

  • Feature extraction and data association for AUV concurrent mapping and localisation

    I. Tena Ruiz;Y. Petillot;D.M. Lane;C. Salson

  • A 2D visual servoing for underwater vehicle station keeping

    J.-F. Lots;D.M. Lane;E. Trucco;F. Chaumette

  • Automatic indexing of underwater survey video: algorithm and benchmarking method

    K. Lebart;C. Smith;E. Trucco;D.M. Lane

  • Two novel approaches for unmanned underwater vehicle path planning: constrained optimisation and semi-infinite constrained optimisation

    Yongji Wang;David M. Lane;Gavin J. Falconer

  • A 2-D visual servoing for underwater vehicle station keeping

    Jean-François Lots;David M. Lane;Emanuele Trucco;François Chaumette

Frequent Co-Authors

Yvan Petillot
Yvan Petillot Heriot-Watt University
Emanuele Trucco
Emanuele Trucco University of Dundee
Neil Robertson
Neil Robertson University of Edinburgh
Yongji Wang
Yongji Wang Huazhong University of Science and Technology
Miquel Canals
Miquel Canals University of Barcelona
Jozée Sarrazin
Jozée Sarrazin University of Western Brittany
François Chaumette
François Chaumette University of Rennes
John E. Fletcher
John E. Fletcher University of New South Wales
Giorgio Bartolini
Giorgio Bartolini Consiglio Nazionale delle Ricerche - CNR
Antonio M. Pascoal
Antonio M. Pascoal Instituto Superior Técnico

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