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Engineering and Technology
Netherlands
2026

D-Index & Metrics

Engineering and Technology

D-Index
81
Citations
30972
World Ranking
483
National Ranking
12

Bart De Schutter 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 Bart De Schutter 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: 749 publications — 99th percentile

99% of scientists in this discipline score the same or lower.

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

Bart De Schutter 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 Bart De Schutter 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: 81 D-Index — 95th percentile

95% 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

  • 2026 - Research.com Engineering and Technology in Netherlands Leader Award
  • 2025 - Research.com Engineering and Technology in Netherlands Leader Award
  • 2019 - IEEE Fellow For contributions to optimal control of discrete-event and hybrid systems

Overview

Bart De Schutter is affiliated with Delft University of Technology in the Netherlands. Their research primarily focuses on the field of Engineering, with significant contributions to areas such as Control and Systems Engineering, Electrical and Electronic Engineering, and Automotive Engineering. Their work also spans Computational Theory and Mathematics, as well as Computer Networks and Communications.

The main topics addressed in their research include:

  • Advanced Control Systems Optimization
  • Traffic control and management
  • Transportation Planning and Optimization
  • Traffic Prediction and Management Techniques
  • Control Systems and Identification
  • Fault Detection and Control Systems
  • Railway Systems and Energy Efficiency

Bart De Schutter has participated in numerous publications, frequently contributing to venues including:

  • IEEE Transactions on Intelligent Transportation Systems
  • arXiv (Cornell University)
  • IFAC-PapersOnLine
  • IEEE Transactions on Automatic Control
  • Automatica

A selection of notable recent papers includes:

  • "Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark," 2020, arXiv (Cornell University)
  • "Adaptive Prescribed Performance Asymptotic Tracking for High-Order Odd-Rational-Power Nonlinear Systems," 2022, IEEE Transactions on Automatic Control
  • "Nonrecursive Control for Formation-Containment of HFV Swarms With Dynamic Event-Triggered Communication," 2022, IEEE Transactions on Industrial Informatics
  • "Robust Optimal Control for Demand Side Management of Multi-Carrier Microgrids," 2022, IEEE Transactions on Automation Science and Engineering
  • "Logic-based distributed switching control for agents in power-chained form with multiple unknown control directions," 2022, Automatica

Collaboration has been a significant aspect of their career, with frequent coauthors including Cristina Olaverri-Monreal, Silvia Siri, Simona Sacone, Matthew Barth, and Yaobin Chen.

Bart De Schutter was recognized as an IEEE Fellow in 2019 for contributions to optimal control of discrete-event and hybrid systems.

Best Publications

  • A Comprehensive Survey of Multiagent Reinforcement Learning

    L. Busoniu;R. Babuska;B. De Schutter

  • Reinforcement Learning and Dynamic Programming Using Function Approximators

    Lucian Busoniu;Robert Babuska;Bart De Schutter;Damien Ernst

  • Brief Equivalence of hybrid dynamical models

    W. P. M. H. Heemels;B. De Schutter;A. Bemporad

  • Multi-agent Reinforcement Learning: An Overview

    Lucian Buşoniu;Robert Babuška;Bart De Schutter

  • Model predictive control for optimal coordination of ramp metering and variable speed limits

    Andreas Hegyi;Bart De Schutter;Hans Hellendoorn

  • Forecasting spot electricity prices: Deep learning approaches and empirical comparison of traditional algorithms

    Jesus Lago;Fjo De Ridder;Bart De Schutter

  • Optimal coordination of variable speed limits to suppress shock waves

    A. Hegyi;Bart De Schutter;J. Hellendoorn

  • Brief Model predictive control for max-plus-linear discrete event systems

    Bart De Schutter;Ton Van Den Boom

  • Stability Analysis and Nonlinear Observer Design using Takagi-Sugeno Fuzzy Models

    Robert Babuska;Bart De Schutter;Zsfia Lendek;T. M. Guerra

  • Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark

    Jesus Lago;Grzegorz Marcjasz;Bart De Schutter;Rafał Weron

  • DAISY : A database for identification of systems

    Bart De Moor;P De Gersem;Bart De Schutter;W Favoreel

  • Deep convolutional neural networks for detection of rail surface defects

    Shahrzad Faghih-Roohi;Siamak Hajizadeh;Alfredo Nunez;Robert Babuska

  • Residential Demand Response of Thermostatically Controlled Loads Using Batch Reinforcement Learning

    Frederik Ruelens;Bert J. Claessens;Stijn Vandael;Bart De Schutter

  • Multi-agent model predictive control for transportation networks: Serial versus parallel schemes

    R. R. Negenborn;B. De Schutter;J. Hellendoorn

  • Demand Response With Micro-CHP Systems

    Michiel Houwing;Rudy R Negenborn;Bart De Schutter

  • Optimal traffic light control for a single intersection

    B. De Schutter;B. De Moor

  • Accelerated gradient methods and dual decomposition in distributed model predictive control

    Pontus Giselsson;Minh Dang Doan;TamáS Keviczky;Bart De Schutter

  • Distributed model predictive control of irrigation canals

    Rudy R. Negenborn;Peter-Jules van Overloop;Tamás Keviczky;Bart De Schutter

  • Model predictive control for ramp metering of motorway traffic: A case study

    T. Bellemans;B. De Schutter;B. De Moor

  • Proceedings of Thirtieth AAAI Conference on Artificial Intelligence

    Lukáš Chrpa;Bart De Schutter;Daniele Magazzeni;Thomas L. McCluskey

  • Model predictive control for perturbed continuous piecewise affine systems with bounded disturbances

    I. Necoara;B. De Schutter;T.J.J. van den Boom;J. Hellendoorn

  • Multi-agent model predictive control for transportation networks: serial versus parallel schemes

    Rudy R. Negenborn;Bart De Schutter;Hans Hellendoorn

Frequent Co-Authors

Hans Hellendoorn
Hans Hellendoorn Delft University of Technology
Robert Babuska
Robert Babuska Delft University of Technology
Bart De Moor
Bart De Moor KU Leuven
Bin Ning
Bin Ning Beijing Jiaotong University
Damien Ernst
Damien Ernst University of Liège
Rudy R. Negenborn
Rudy R. Negenborn Delft University of Technology
Shu Lin
Shu Lin University of California, Davis
Andreas Hegyi
Andreas Hegyi Delft University of Technology
Simone Baldi
Simone Baldi Southeast University
Alessandro Abate
Alessandro Abate University of Oxford

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