World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
36
Citations
5064
World Ranking
11312
National Ranking
4666

Thomas Plötz 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 Thomas Plötz 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: 125 publications — 17th percentile

17% of scientists in this discipline score the same or lower.

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

Thomas Plötz 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 Thomas Plötz 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: 36 D-Index — 23rd percentile

23% of scientists in this discipline score the same or lower.

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

Overview

Thomas Plötz is affiliated with the Georgia Institute of Technology in the United States. Their research primarily spans the field of Computer Science, with a focus on subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications, Biomedical Engineering, and Computer Science Applications.

The main topics addressed in their work include Context-Aware Activity Recognition Systems, Human Pose and Action Recognition, Anomaly Detection Techniques and Applications, IoT and Edge/Fog Computing, Non-Invasive Vital Sign Monitoring, Mobile Crowdsensing and Crowdsourcing, and Technology Use by Older Adults.

Plötz's publications appear frequently in several venues, most notably in the Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, arXiv (Cornell University), Sensors, ACM Transactions on Computing for Healthcare, and ACM Transactions on Interactive Intelligent Systems.

Notable recent papers include:

  • IMUTube, 2020, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies
  • Assessing the State of Self-Supervised Human Activity Recognition Using Wearables, 2022, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies
  • Explainable Activity Recognition for Smart Home Systems, 2023, ACM Transactions on Interactive Intelligent Systems
  • Estimation of Instantaneous Oxygen Uptake During Exercise and Daily Activities Using a Wearable Cardio-Electromechanical and Environmental Sensor, 2020, IEEE Journal of Biomedical and Health Informatics
  • Approaching the Real-World, 2021, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies

Plötz has collaborated frequently with several co-authors, including:

  • Hyeokhyen Kwon
  • Gregory D. Abowd
  • Harish Haresamudram
  • Zikang Leng
  • Sonia Chernova

Best Publications

  • Deep, convolutional, and recurrent models for human activity recognition using wearables

    Nils Y. Hammerla;Shane Halloran;Thomas Plötz

  • Ensembles of Deep LSTM Learners for Activity Recognition using Wearables

    Yu Guan;Thomas Plötz

  • Feature learning for activity recognition in ubiquitous computing

    Thomas Plötz;Nils Y. Hammerla;Patrick Olivier

  • Markov models for offline handwriting recognition: a survey

    Thomas Plötz;Gernot A. Fink

  • The mobile fitness coach: Towards individualized skill assessment using personalized mobile devices

    Matthias Kranz;Andreas MöLler;Nils Hammerla;Stefan Diewald

  • Early detection of health and welfare compromises through automated detection of behavioural changes in pigs

    Stephen G. Matthews;Amy L. Miller;James Clapp;Thomas Plötz

  • PD disease state assessment in naturalistic environments using deep learning

    Nils Y. Hammerla;James M. Fisher;Peter Andras;Lynn Rochester

  • Optimising sampling rates for accelerometer-based human activity recognition

    Aftab Khan;Nils Hammerla;Sebastian Mellor;Thomas Plötz

  • Automated tracking to measure behavioural changes in pigs for health and welfare monitoring.

    Stephen G. Matthews;Amy L. Miller;Thomas PlÖtz;Thomas PlÖtz;Ilias Kyriazakis

  • Multi-modal anchoring for human–robot interaction

    Jannik Fritsch;Marcus Kleinehagenbrock;Sebastian Lang;Thomas Plötz

  • Automatic assessment of problem behavior in individuals with developmental disabilities

    Thomas Plötz;Nils Y. Hammerla;Agata Rozga;Andrea Reavis

  • Using unlabeled data in a sparse-coding framework for human activity recognition

    Sourav Bhattacharya;Petteri Nurmi;Nils Hammerla;Thomas Plötz

  • Movement recognition technology as a method of assessing spontaneous general movements in high risk infants.

    Claire Marcroft;Claire Marcroft;Aftab Khan;Nicholas D. Embleton;Michael Trenell

  • Rapid specification and automated generation of prompting systems to assist people with dementia

    Jesse Hoey;Thomas Plötz;Dan Jackson;Andrew Monk

  • ClimbAX: skill assessment for climbing enthusiasts

    Cassim Ladha;Nils Y. Hammerla;Patrick Olivier;Thomas Plötz

  • IMUTube: Automatic Extraction of Virtual on-body Accelerometry from Video for Human Activity Recognition

    Hyeokhyen Kwon;Catherine Tong;Harish Haresamudram;Yan Gao

  • Dog's life: wearable activity recognition for dogs

    Cassim Ladha;Nils Hammerla;Emma Hughes;Patrick Olivier

  • Masked reconstruction based self-supervision for human activity recognition

    Harish Haresamudram;Apoorva Beedu;Varun Agrawal;Patrick L. Grady

  • Let's (not) stick together: pairwise similarity biases cross-validation in activity recognition

    Nils Y. Hammerla;Thomas Plötz

  • Assessing the State of Self-Supervised Human Activity Recognition Using Wearables

    Unknown

  • On attention models for human activity recognition.

    Vishvak S. Murahari;Thomas Plötz

  • Deep Learning for Human Activity Recognition in Mobile Computing

    Thomas Plotz;Yu Guan

  • GymSkill: A personal trainer for physical exercises

    Andreas Moller;Luis Roalter;Stefan Diewald;Johannes Scherr

  • Prediction of Mood Instability with Passive Sensing

    Mehrab Bin Morshed;Koustuv Saha;Richard Li;Sidney K. D'Mello

  • On the role of features in human activity recognition

    Harish Haresamudram;David V. Anderson;Thomas Plötz

  • Occupancy monitoring using environmental & context sensors and a hierarchical analysis framework

    Aftab Khan;James Nicholson;Sebastian Mellor;Daniel Jackson

Frequent Co-Authors

Gernot A. Fink
Gernot A. Fink TU Dortmund University
Patrick Olivier
Patrick Olivier Monash University
Gregory D. Abowd
Gregory D. Abowd Northeastern University
Ilias Kyriazakis
Ilias Kyriazakis Queen's University Belfast
Irfan Essa
Irfan Essa Georgia Institute of Technology
David Kirk
David Kirk Newcastle University
Stephen J. McKenna
Stephen J. McKenna University of Dundee
Munmun De Choudhury
Munmun De Choudhury Georgia Institute of Technology
Kristof Van Laerhoven
Kristof Van Laerhoven University of Siegen
Stephen G. Matthews
Stephen G. Matthews University of Toronto

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