World's Best Scientists 2026 revealed!
Carl Edward Rasmussen

Carl Edward Rasmussen

D-Index & Metrics

Computer Science

D-Index
56
Citations
75803
World Ranking
3925
National Ranking
237

Carl Edward Rasmussen publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Carl Edward Rasmussen sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 138 publications — 22nd percentile

22% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Carl Edward Rasmussen D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Carl Edward Rasmussen sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 56 D-Index — 72nd percentile

72% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Carl Edward Rasmussen is affiliated with the University of Cambridge in the United Kingdom. Their research primarily focuses on computer science with a specialization in artificial intelligence. The main areas of study within this field include control and systems engineering, computational theory and mathematics, global and planetary change, as well as statistics and probability.

Their work emphasizes several core topics:

  • Gaussian Processes and Bayesian Inference
  • Control Systems and Identification
  • Atmospheric and Environmental Gas Dynamics
  • Machine Learning and Data Classification
  • Statistical Methods and Inference
  • Computational Drug Discovery Methods
  • Advanced Multi-Objective Optimization Algorithms

Carl Edward Rasmussen has contributed multiple research papers, with publications mostly appearing in the arXiv repository affiliated with Cornell University as well as specialized journals such as the Journal of Engineering for Gas Turbines and Power. Some recent papers include:

  • Convergence of Sparse Variational Inference in Gaussian Processes Regression, 2020, arXiv (Cornell University)
  • Bayesian Machine Learning for the Prognosis of Combustion Instabilities From Noise, 2021, Journal of Engineering for Gas Turbines and Power
  • The Promises and Pitfalls of Deep Kernel Learning, 2021, arXiv (Cornell University)
  • Variational Orthogonal Features, 2020, arXiv (Cornell University)

Frequent collaborators in their research include David R. Burt, Mark van der Wilk, Miguel García-Ortegón, Srijit Seal, and Andreas Bender. This network indicates a collaborative approach across various subfields within machine learning and control systems.

The venues where Rasmussen frequently publishes comprise:

  • arXiv (Cornell University)
  • Journal of Engineering for Gas Turbines and Power
  • Journal of Cheminformatics
  • Chemical Science
  • NERC Open Research Archive (Natural Environment Research Council)

This profile reflects an academic career centered on advancing methods in Gaussian processes and Bayesian inference, with intersections in control engineering and environmental applications. The focus on statistical and computational methodologies aligns with ongoing developments in machine learning and optimization algorithms within a scientific framework.

Best Publications

  • Gaussian Processes for Machine Learning

    Carl Edward Rasmussen;Christopher K I Williams

  • Gaussian processes in machine learning

    Carl Edward Rasmussen

  • Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)

    Carl Edward Rasmussen;Christopher K. I. Williams

  • A Unifying View of Sparse Approximate Gaussian Process Regression

    Joaquin Quiñonero-Candela;Carl Edward Rasmussen

  • Gaussian Processes for Regression

    Christopher K. I. Williams;Carl Edward Rasmussen

  • The Infinite Gaussian Mixture Model

    Carl Edward Rasmussen

  • PILCO: A Model-Based and Data-Efficient Approach to Policy Search

    Marc Deisenroth;Carl E. Rasmussen

  • Gaussian Processes for Machine Learning (GPML) Toolbox

    Carl Edward Rasmussen;Hannes Nickisch

  • The Infinite Hidden Markov Model

    Matthew J. Beal;Zoubin Ghahramani;Carl E. Rasmussen

  • Gaussian Processes for Data-Efficient Learning in Robotics and Control

    Marc Peter Deisenroth;Dieter Fox;Carl Edward Rasmussen

  • Evaluation of gaussian processes and other methods for non-linear regression

    Geoffrey Hinton;Carl Edward Rasmussen

  • Infinite Mixtures of Gaussian Process Experts

    Carl E. Rasmussen;Zoubin Ghahramani

  • Sparse Spectrum Gaussian Process Regression

    Miguel Lázaro-Gredilla;Joaquin Quiñonero-Candela;Carl Edward Rasmussen;Aníbal R. Figueiras-Vidal

  • Approximations for Binary Gaussian Process Classification

    Hannes Nickisch;Carl Edward Rasmussen

  • Assessing Approximate Inference for Binary Gaussian Process Classification

    Malte Kuss;Carl Edward Rasmussen

  • Warped Gaussian Processes

    Edward Snelson;Zoubin Ghahramani;Carl E. Rasmussen

  • Derivative Observations in Gaussian Process Models of Dynamic Systems

    E. Solak;R. Murray-smith;W. E. Leithead;D. J. Leith

  • Gaussian Process Priors with Uncertain Inputs Application to Multiple-Step Ahead Time Series Forecasting

    Agathe Girard;Carl Edward Rasmussen;Joaquin Quiñonero Candela;Roderick Murray-Smith

  • Additive Gaussian Processes

    David K Duvenaud;Hannes Nickisch;Carl E. Rasmussen

  • Gaussian process model based predictive control

    J. Kocijan;R. Murray-Smith;C.E. Rasmussen;A. Girard

  • Gaussian Processes in Reinforcement Learning

    Malte Kuss;Carl E. Rasmussen

Frequent Co-Authors

Marc Peter Deisenroth
Marc Peter Deisenroth University College London
Zoubin Ghahramani
Zoubin Ghahramani University of Cambridge
Roderick Murray-Smith
Roderick Murray-Smith University of Glasgow
Jan Peters
Jan Peters Technical University of Darmstadt
Lars Kai Hansen
Lars Kai Hansen Technical University of Denmark
Bernhard Schölkopf
Bernhard Schölkopf Max Planck Institute for Intelligent Systems
Thomas B. Schön
Thomas B. Schön Uppsala University
Jan Larsen
Jan Larsen Technical University of Denmark
Jan Maciejowski
Jan Maciejowski University of Cambridge
Andreas S. Tolias
Andreas S. Tolias Baylor College of Medicine

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