World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
41
Citations
7135
World Ranking
8839
National Ranking
10

Ales Ude 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 Ales Ude 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: 228 publications — 56th percentile

56% of scientists in this discipline score the same or lower.

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

Ales Ude 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 Ales Ude 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: 41 D-Index — 40th percentile

40% of scientists in this discipline score the same or lower.

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

Overview

Ales Ude is affiliated with the Jožef Stefan Institute in Slovenia and contributes extensively to the fields of Engineering and Computer Science. Their research focuses on several main disciplines, including Control and Systems Engineering, Industrial and Manufacturing Engineering, Biomedical Engineering, Artificial Intelligence, and Computer Vision and Pattern Recognition.

The primary research topics covered in their work include Robot Manipulation and Learning, Manufacturing Process and Optimization, Flexible and Reconfigurable Manufacturing Systems, Human Pose and Action Recognition, Reinforcement Learning in Robotics, Prosthetics and Rehabilitation Robotics, and Robotic Locomotion and Control.

Recent papers authored or co-authored by Ales Ude highlight diverse areas of robotics and machine learning. Among these are:

  • Smart hardware integration with advanced robot programming technologies for efficient reconfiguration of robot workcells (2020, Robotics and Computer-Integrated Manufacturing)
  • Mechanical design and friction modelling of a cable-driven upper-limb exoskeleton (2022, Mechanism and Machine Theory)
  • Training of deep neural networks for the generation of dynamic movement primitives (2020, Neural Networks)
  • Robot skill learning in latent space of a deep autoencoder neural network (2020, Robotics and Autonomous Systems)
  • Transfer learning in robotics: An upcoming breakthrough? A review of promises and challenges (2024, The International Journal of Robotics Research)

Ales Ude frequently collaborates with several co-authors, including Mihael Simonič, Bojan Nemec, Andrej Gams, Miha Deniša, and Rok Pahič. These collaborative efforts contribute to the breadth and depth of their research output.

The scientist's work has been published repeatedly in notable venues such as the 20th International Conference on Advanced Robotics (ICAR), Zenodo (CERN European Organization for Nuclear Research), Robotics and Computer-Integrated Manufacturing, arXiv (Cornell University), and Applied Sciences.

Best Publications

  • Task-Specific Generalization of Discrete and Periodic Dynamic Movement Primitives

    Aleš Ude;Andrej Gams;Tamim Asfour;Jun Morimoto

  • Using humanoid robots to study human behavior

    C.G. Atkeson;J.G. Hale;F. Pollick;M. Riley

  • CB: A Humanoid Research Platform for Exploring NeuroScience

    G. Cheng;Sang-Ho Hyon;J. Morimoto;A. Ude

  • Programming full-body movements for humanoid robots by observation

    Aleš Ude;Christopher G. Atkeson;Marcia Riley

  • The meaning of action: a review on action recognition and mapping

    Volker Krüger;Danica Kragic;Aleš Ude;Christopher Geib

  • Orientation in Cartesian space dynamic movement primitives

    Ales Ude;Bojan Nemec;Tadej Petric;Jun Morimoto

  • Coupling Movement Primitives: Interaction With the Environment and Bimanual Tasks

    Andrej Gams;Bojan Nemec;Auke Jan Ijspeert;Ales Ude

  • Object-action complexes: Grounded abstractions of sensory-motor processes

    Norbert Krüger;Christopher W. Geib;Justus H. Piater;Ronald P. A. Petrick

  • Adaptive Control of Exoskeleton Robots for Periodic Assistive Behaviours Based on EMG Feedback Minimisation.

    Luka Peternel;Tomoyuki Noda;Tadej Petrič;Aleš Ude

  • Adaptation of manipulation skills in physical contact with the environment to reference force profiles

    Fares J. Abu-Dakka;Bojan Nemec;Jimmy A. JØrgensen;Thiusius R. Savarimuthu

  • Learning Actions from Observations

    Volker Kruger;Dennis Herzog;Sanmohan Baby;Aleš Ude

  • The Karlsruhe Humanoid Head

    T. Asfour;K. Welke;P. Azad;A. Ude

  • On-line motion synthesis and adaptation using a trajectory database

    Denis Forte;Andrej Gams;Jun Morimoto;Aleš Ude

  • Learning to pour with a robot arm combining goal and shape learning for dynamic movement primitives

    Minija Tamosiunaite;Bojan Nemec;Aleš Ude;Florentin WöRgöTter

  • Planning of joint trajectories for humanoid robots using B-spline wavelets

    A. Ude;C.G. Atkeson;M. Riley

  • Enabling real-time full-body imitation: a natural way of transferring human movement to humanoids

    M. Riley;A. Ude;K. Wade;C.G. Atkeson

  • A Simple Ontology of Manipulation Actions Based on Hand-Object Relations

    F. Worgotter;E. E. Aksoy;N. Kruger;J. Piater

  • Trajectory generation from noisy positions of object features for teaching robot paths

    Aleš Ude

  • Learning Compliant Movement Primitives Through Demonstration and Statistical Generalization

    Miha Denisa;Andrej Gams;Ales Ude;Tadej Petric

  • Automatic Generation of Kinematic Models for the Conversion of Human Motion Capture Data into Humanoid Robot Motion

    Ales Ude;Curtis Man;Marcia Riley;Christopher G. Atkeson

Frequent Co-Authors

Tamim Asfour
Tamim Asfour Karlsruhe Institute of Technology
Gordon Cheng
Gordon Cheng Technical University of Munich
Jun Morimoto
Jun Morimoto Advanced Telecommunications Research Institute International
Christopher G. Atkeson
Christopher G. Atkeson Carnegie Mellon University
Norbert Krüger
Norbert Krüger University of Southern Denmark
Florentin Wörgötter
Florentin Wörgötter University of Göttingen
Rüdiger Dillmann
Rüdiger Dillmann Center for Information Technology
Auke Jan Ijspeert
Auke Jan Ijspeert École Polytechnique Fédérale de Lausanne
Justus Piater
Justus Piater University of Innsbruck
Danica Kragic
Danica Kragic Royal Institute of Technology

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