World's Best Scientists 2026 revealed!
Cyrill Stachniss

Cyrill Stachniss

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Computer Science
Germany
2025

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
83
Citations
36492
World Ranking
419
National Ranking
11

Computer Science

D-Index
84
Citations
36868
World Ranking
830
National Ranking
29

Cyrill Stachniss publication distribution in Electronics and Electrical Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Electronics and Electrical Engineering in 2026. The highlighted bar marks where Cyrill Stachniss sits on this spectrum.

34–53 publications: 24 scientists 54–73 publications: 52 scientists 74–93 publications: 114 scientists 94–113 publications: 203 scientists 114–133 publications: 269 scientists 134–153 publications: 355 scientists 154–173 publications: 403 scientists 174–193 publications: 445 scientists 194–213 publications: 430 scientists 214–233 publications: 431 scientists 234–253 publications: 399 scientists 254–273 publications: 366 scientists 274–293 publications: 335 scientists 294–313 publications: 300 scientists 314–333 publications: 276 scientists 334–353 publications: 250 scientists 354–373 publications: 214 scientists 374–393 publications: 187 scientists 394–413 publications: 152 scientists 414–433 publications: 169 scientists 434–453 publications: 147 scientists 454–473 publications: 111 scientists 474–493 publications: 117 scientists 494–513 publications: 103 scientists 514–533 publications: 99 scientists 534–553 publications: 92 scientists 554–573 publications: 75 scientists 574–593 publications: 58 scientists 594–613 publications: 69 scientists 614–633 publications: 50 scientists 634–653 publications: 62 scientists 654–673 publications: 54 scientists 674–693 publications: 44 scientists 694–713 publications: 37 scientists 714–733 publications: 28 scientists 734–753 publications: 26 scientists 754–773 publications: 26 scientists 774–793 publications: 19 scientists 794–813 publications: 23 scientists 814–833 publications: 20 scientists 834–853 publications: 16 scientists 854–873 publications: 20 scientists 874–893 publications: 11 scientists 894–913 publications: 11 scientists 914–933 publications: 16 scientists 934–953 publications: 13 scientists 954–973 publications: 10 scientists 974–993 publications: 11 scientists 994–1,013 publications: 9 scientists 1,014–1,033 publications: 9 scientists 1,034–1,053 publications: 10 scientists 1,054–1,064 publications: 6 scientists 1,065+ publications: 99 scientists
34 publications 1,065+

This scientist: 371 publications — 71st percentile

71% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,065 publications or more.

Cyrill Stachniss D-index placement in Electronics and Electrical Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Electronics and Electrical Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Cyrill Stachniss sits on this spectrum.

30 D-Index: 178 scientists 31 D-Index: 257 scientists 32 D-Index: 263 scientists 33 D-Index: 262 scientists 34 D-Index: 244 scientists 35 D-Index: 236 scientists 36 D-Index: 211 scientists 37 D-Index: 220 scientists 38 D-Index: 214 scientists 39 D-Index: 214 scientists 40 D-Index: 205 scientists 41 D-Index: 187 scientists 42 D-Index: 194 scientists 43 D-Index: 201 scientists 44 D-Index: 155 scientists 45 D-Index: 189 scientists 46 D-Index: 148 scientists 47 D-Index: 160 scientists 48 D-Index: 134 scientists 49 D-Index: 130 scientists 50 D-Index: 141 scientists 51 D-Index: 156 scientists 52 D-Index: 108 scientists 53 D-Index: 130 scientists 54 D-Index: 112 scientists 55 D-Index: 97 scientists 56 D-Index: 111 scientists 57 D-Index: 102 scientists 58 D-Index: 108 scientists 59 D-Index: 120 scientists 60 D-Index: 103 scientists 61 D-Index: 93 scientists 62 D-Index: 92 scientists 63 D-Index: 74 scientists 64 D-Index: 77 scientists 65 D-Index: 73 scientists 66 D-Index: 64 scientists 67 D-Index: 69 scientists 68 D-Index: 60 scientists 69 D-Index: 39 scientists 70 D-Index: 57 scientists 71 D-Index: 59 scientists 72 D-Index: 46 scientists 73 D-Index: 49 scientists 74 D-Index: 38 scientists 75 D-Index: 35 scientists 76 D-Index: 32 scientists 77 D-Index: 35 scientists 78 D-Index: 31 scientists 79 D-Index: 22 scientists 80 D-Index: 34 scientists 81 D-Index: 31 scientists 82 D-Index: 34 scientists 83 D-Index: 23 scientists 84 D-Index: 18 scientists 85 D-Index: 30 scientists 86 D-Index: 19 scientists 87 D-Index: 19 scientists 88 D-Index: 20 scientists 89 D-Index: 8 scientists 90 D-Index: 17 scientists 91 D-Index: 7 scientists 92 D-Index: 14 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 12 scientists 97 D-Index: 10 scientists 98 D-Index: 10 scientists 99 D-Index: 12 scientists 100 D-Index: 16 scientists 101 D-Index: 5 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 8 scientists 105 D-Index: 9 scientists 106 D-Index: 13 scientists 107 D-Index: 4 scientists 108 D-Index: 5 scientists 109 D-Index: 10 scientists 110 D-Index: 8 scientists 111+ D-Index: 96 scientists
30 D-Index 111+

This scientist: 83 D-Index — 94th percentile

94% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 111 D-Index or more.

Research.com Recognitions

  • 2025 - Research.com Computer Science in Germany Leader Award
  • 2023 - Research.com Computer Science in Germany Leader Award
  • 2022 - Research.com Computer Science in Germany Leader Award

Overview

Cyrill Stachniss is affiliated with the University of Bonn in Germany. Their research spans multiple fields with a focus on engineering and computer science. They have contributed extensively to subfields such as computer vision and pattern recognition, aerospace engineering, plant science, environmental engineering, and geology.

The primary topics of their work include robotics and sensor-based localization, smart agriculture and AI, remote sensing and LiDAR applications, robotic path planning algorithms, 3D surveying and cultural heritage, advanced image and video retrieval techniques, and advanced neural network applications.

Their recent notable publications include:

  • "KISS-ICP: In Defense of Point-to-Point ICP - Simple, Accurate, and Robust Registration If Done the Right Way," 2023, IEEE Robotics and Automation Letters
  • "Moving Object Segmentation in 3D LiDAR Data: A Learning-Based Approach Exploiting Sequential Data," 2021, IEEE Robotics and Automation Letters
  • "Robotic weed control using automated weed and crop classification," 2020, Journal of Field Robotics
  • "Pheno4D: A spatio-temporal dataset of maize and tomato plant point clouds for phenotyping and advanced plant analysis," 2021, PLoS ONE
  • "Towards 3D LiDAR-based semantic scene understanding of 3D point cloud sequences: The SemanticKITTI Dataset," 2021, The International Journal of Robotics Research

The frequent co-authors who have collaborated on a significant number of publications with Cyrill Stachniss include:

  • Jens Behley
  • Federico Magistri
  • Xieyuanli Chen
  • Marija Popović
  • Tiziano Guadagnino

Publication venues where Cyrill Stachniss has contributed the most encompass arXiv (Cornell University), IEEE Robotics and Automation Letters, and the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) for the years 2021 and 2022. Other venues include Computers and Electronics in Agriculture.

  • arXiv (Cornell University)
  • IEEE Robotics and Automation Letters
  • 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  • 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  • Computers and Electronics in Agriculture

Best Publications

  • OctoMap: an efficient probabilistic 3D mapping framework based on octrees

    Armin Hornung;Kai M. Wurm;Maren Bennewitz;Cyrill Stachniss

  • Improved Techniques for Grid Mapping With Rao-Blackwellized Particle Filters

    G. Grisetti;C. Stachniss;W. Burgard

  • SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences

    Jens Behley;Martin Garbade;Andres Milioto;Jan Quenzel

  • A Tutorial on Graph-Based SLAM

    G Grisetti;R Kümmerle;C Stachniss;W Burgard

  • Coordinated multi-robot exploration

    W. Burgard;M. Moors;C. Stachniss;F.E. Schneider

  • RangeNet ++: Fast and Accurate LiDAR Semantic Segmentation

    Andres Milioto;Ignacio Vizzo;Jens Behley;Cyrill Stachniss

  • Improving Grid-based SLAM with Rao-Blackwellized Particle Filters by Adaptive Proposals and Selective Resampling

    G. Grisettiyz;C. Stachniss;W. Burgard

  • Information Gain-based Exploration Using Rao-Blackwellized Particle Filters

    Cyrill Stachniss;Giorgio Grisetti;Wolfram Burgard

  • SuMa++: Efficient LiDAR-based Semantic SLAM

    Xieyuanli Chen;Andres Milioto;Emanuele Palazzolo;Philippe Giguere

  • Efficient Surfel-Based SLAM using 3D Laser Range Data in Urban Environments

    Jens Behley;Cyrill Stachniss

  • On measuring the accuracy of SLAM algorithms

    Rainer Kümmerle;Bastian Steder;Christian Dornhege;Michael Ruhnke

  • KISS-ICP: In Defense of Point-to-Point ICP – Simple, Accurate, and Robust Registration If Done the Right Way

    Unknown

  • UAV-based crop and weed classification for smart farming

    Philipp Lottes;Raghav Khanna;Johannes Pfeifer;Roland Siegwart

  • Real-Time Semantic Segmentation of Crop and Weed for Precision Agriculture Robots Leveraging Background Knowledge in CNNs

    Andres Milioto;Philipp Lottes;Cyrill Stachniss

  • A tree parameterization for efficiently computing maximum likelihood maps using gradient descent

    Giorgio Grisetti;Cyrill Stachniss;Slawomir Grzonka;Wolfram Burgard

  • Robust map optimization using dynamic covariance scaling

    Pratik Agarwal;Gian Diego Tipaldi;Luciano Spinello;Cyrill Stachniss

  • Agricultural robot dataset for plant classification, localization and mapping on sugar beet fields

    Nived Chebrolu;Philipp Lottes;Alexander Schaefer;Wera Winterhalter

  • Coordinated multi-robot exploration using a segmentation of the environment

    K.M. Wurm;C. Stachniss;W. Burgard

  • Supervised Learning of Places from Range Data using AdaBoost

    O.M. Mozos;C. Stachniss;W. Burgard

  • Nonlinear Constraint Network Optimization for Efficient Map Learning

    G. Grisetti;C. Stachniss;W. Burgard

  • Hierarchical optimization on manifolds for online 2D and 3D mapping

    Giorgio Grisetti;Rainer Kummerle;Cyrill Stachniss;Udo Frese

  • An Efficient Probabilistic 3D Mapping Framework Based on Octrees

    Armin Hornung;Kai M. Wurm;Maren Bennewitz;Cyrill Stachniss

Frequent Co-Authors

Wolfram Burgard
Wolfram Burgard University of Technology Nuremberg
Giorgio Grisetti
Giorgio Grisetti Sapienza University of Rome
Oliver Brock
Oliver Brock Technical University of Berlin
Maren Bennewitz
Maren Bennewitz University of Bonn
Sven Behnke
Sven Behnke University of Bonn
Juan Nieto
Juan Nieto Microsoft (United States)
Jürgen Sturm
Jürgen Sturm Google (United States)
Achim Walter
Achim Walter ETH Zurich
Matthias Teschner
Matthias Teschner University of Freiburg

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