World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
42
Citations
7896
World Ranking
6493
National Ranking
342

Andry Rakotonirainy 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 Andry Rakotonirainy 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: 315 publications — 78th percentile

78% of scientists in this discipline score the same or lower.

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

Andry Rakotonirainy 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 Andry Rakotonirainy 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: 42 D-Index — 35th percentile

35% of scientists in this discipline score the same or lower.

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

Overview

Andry Rakotonirainy is affiliated with the Queensland University of Technology in Australia. Their research spans various aspects of engineering and psychology, focusing particularly on automotive systems and road safety.

Their publication record includes papers primarily in the fields of engineering and psychology, with significant work in automotive engineering, social psychology, safety, risk, reliability and quality, transportation, and computer vision and pattern recognition.

The main topics of their work cover:

  • Human-Automation Interaction and Safety
  • Traffic and Road Safety
  • Transportation and Mobility Innovations
  • Autonomous Vehicle Technology and Safety
  • Traffic Prediction and Management Techniques
  • Urban Transport and Accessibility
  • Vehicle emissions and performance

Frequent co-authors include:

  • Mohammed Elhenawy
  • Sébastien Glaser
  • Mahmoud Masoud
  • Huthaifa I. Ashqar
  • Xiaomeng Li

Rakotonirainy has published in a variety of venues. The most common publication venues are:

  • Transportation Research Part F Traffic Psychology and Behaviour
  • SSRN Electronic Journal
  • arXiv (Cornell University)
  • IEEE Access
  • Accident Analysis & Prevention

Recent papers include:

  • Automatic Emotion Recognition Using Temporal Multimodal Deep Learning, 2020, IEEE Access
  • A Dual Learning Model for Vehicle Trajectory Prediction, 2020, IEEE Access
  • Perception Analysis of E-Scooter Riders and Non-Riders in Riyadh, Saudi Arabia: Survey Outputs, 2021, Sustainability
  • Effects of different non-driving-related-task display modes on drivers' eye-movement patterns during take-over in an automated vehicle, 2020, Transportation Research Part F Traffic Psychology and Behaviour
  • Crash severity analysis of vulnerable road users using machine learning, 2021, PLoS ONE

Best Publications

  • Modeling Context Information in Pervasive Computing Systems

    Karen Henricksen;Jadwiga Indulska;Andry Rakotonirainy

  • Sustainable Business Models: A Review

    Saeed Nosratabadi;Amir Mosavi;Shahaboddin Shamshirband;Edmundas Kazimieras Zavadskas

  • Experiences in using CC/PP in context-aware systems

    Jadwiga Indulska;Ricky Robinson;Andry Rakotonirainy;Karen Henricksen

  • A survey of research on context-aware homes

    Sven Meyer;Andry Rakotonirainy

  • Generating context management infrastructure from high level context models

    Karen Henricksen;Jadwiga Indulska;Andry Rakotonirainy

  • Driving performance impairments due to hypovigilance on monotonous roads

    Grégoire S. Larue;Andry Rakotonirainy;Anthony N. Pettitt

  • Affordable visual driver monitoring system for fatigue and monotony

    T. Brandt;R. Stemmer;A. Rakotonirainy

  • Automatic Driver Stress Level Classification Using Multimodal Deep Learning

    Mohammad Naim Rastgoo;Bahareh Nakisa;Frederic Maire;Andry Rakotonirainy

  • Infrastructure for pervasive computing: Challenges

    Karen Henricksen;Jadwiga Indulska;Andry Rakotonirainy

  • Long Short Term Memory Hyperparameter Optimization for a Neural Network Based Emotion Recognition Framework

    Bahareh Nakisa;Mohammad Naim Rastgoo;Andry Rakotonirainy;Frederic Maire

  • Perception, information processing and modeling: Critical stages for autonomous driving applications

    Dominique Gruyer;Valentin Magnier;Karima Hamdi;Laurène Claussmann

  • A Critical Review of Proactive Detection of Driver Stress Levels Based on Multimodal Measurements

    Mohammad Naim Rastgoo;Bahareh Nakisa;Andry Rakotonirainy;Vinod Chandran

  • A comparative analysis of e-scooter and e-bike usage patterns:Findings from the City of Austin, TX

    Mohammed Hamad Almannaa;Huthaifa I. Ashqar;Mohammed Elhenawy;Mahmoud Masoud

  • Pervasive Technology and Public Transport: Opportunities Beyond Telematics

    T. D. Camacho;M. Foth;A. Rakotonirainy

  • Context-oriented programming

    Roger Keays;Andry Rakotonirainy

  • Older drivers' crashes in Queensland, Australia

    Andry Rakotonirainy;Dale Steinhardt;Patricia Delhomme;Millie Darvell

  • Automatic Emotion Recognition Using Temporal Multimodal Deep Learning

    Bahareh Nakisa;Mohammad Naim Rastgoo;Andry Rakotonirainy;Frederic Maire

  • Assessing driver acceptance of Intelligent Transport Systems in the context of railway level crossings

    Grégoire S. Larue;Andry Rakotonirainy;Narelle L. Haworth;Millie Darvell

  • A Dual Learning Model for Vehicle Trajectory Prediction

    Mahrokh Khakzar;Andry Rakotonirainy;Andy Bond;Sepehr G. Dehkordi

  • Examining the effects of an eco-driving message on driver distraction

    Hossein Rouzikhah;Mark King;Andry Rakotonirainy

  • Collision Pattern Modeling and Real-Time Collision Detection at Road Intersections

    F.D. Salim;Seng Wai Loke;A. Rakotonirainy;B. Srinivasan

  • Collision risk management of cognitively distracted drivers in a car-following situation

    Xiaomeng Li;Xiaomeng Li;Oscar Oviedo-Trespalacios;Andry Rakotonirainy;Xuedong Yan

  • Three social car visions to improve driver behaviour

    Andry Rakotonirainy;Ronald Schroeter;Alessandro Soro

Frequent Co-Authors

Seng Wai Loke
Seng Wai Loke Deakin University
Shonali Krishnaswamy
Shonali Krishnaswamy Monash University
Jadwiga Indulska
Jadwiga Indulska University of Queensland
Luis Ferreira
Luis Ferreira University of Queensland
Hesham A. Rakha
Hesham A. Rakha Virginia Tech
Arkady Zaslavsky
Arkady Zaslavsky Deakin University
Anthony N. Pettitt
Anthony N. Pettitt Queensland University of Technology
Barry C. Watson
Barry C. Watson Queensland University of Technology
Raphael H Grzebieta
Raphael H Grzebieta University of New South Wales
Ann Williamson
Ann Williamson University of New South Wales

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