World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
55
Citations
11909
World Ranking
4323
National Ranking
2029

Marjorie Skubic 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 Marjorie Skubic 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: 275 publications — 68th percentile

68% of scientists in this discipline score the same or lower.

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

Marjorie Skubic 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 Marjorie Skubic 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: 55 D-Index — 71st percentile

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

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

Research.com Recognitions

  • 2018 - Fellow of the Indian National Academy of Engineering (INAE)

Overview

Marjorie Skubic is affiliated with the University of Missouri in the United States. Their research spans multiple disciplines, primarily focusing on Medicine and Computer Science. Within these fields, they have contributed to subfields such as Computer Vision and Pattern Recognition, Biomedical Engineering, Cardiology and Cardiovascular Medicine, Physical Therapy, Sports Therapy and Rehabilitation, and Surgery.

The scientist's work covers a variety of topics, including:

  • Context-Aware Activity Recognition Systems
  • Non-Invasive Vital Sign Monitoring
  • Balance, Gait, and Falls Prevention
  • Stroke Rehabilitation and Recovery
  • Heart Rate Variability and Autonomic Control
  • Technology Use by Older Adults
  • Time Series Analysis and Forecasting

Their frequent co-authors include Mihail Popescu, James M. Keller, Laurel Despins, Rachel Proffitt, and Mengxuan Ma.

Marjorie Skubic has published multiple papers in various venues, some of which include:

  • "Explainable Fall Risk Prediction in Older Adults Using Gait and Geriatric Assessments," 2022, Frontiers in Digital Health
  • "Non-Invasive Heart Rate Estimation From Ballistocardiograms Using Bidirectional LSTM Regression," 2021, IEEE Journal of Biomedical and Health Informatics
  • "Technology for Healthy Independent Living: Creating a Tailored In-Home Sensor System for Older Adults and Family Caregivers," 2020, Journal of Gerontological Nursing
  • "Early Detection of Health Changes in the Elderly Using In-Home Multi-Sensor Data Streams," 2021, ACM Transactions on Computing for Healthcare
  • "Using Sensor Signals in the Early Detection of Heart Failure: A Case Study," 2020, Journal of Gerontological Nursing

The scientist has a notable publication presence in venues such as Innovation in Aging, Journal of Gerontological Nursing, American Journal of Occupational Therapy, IEEE Journal of Biomedical and Health Informatics, and the 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Marjorie Skubic was recognized as a Fellow of the Indian National Academy of Engineering (INAE) in 2018.

Best Publications

  • Older adults' attitudes towards and perceptions of ‘smart home’ technologies: a pilot study

    George Demiris;Marilyn J. Rantz;Myra A. Aud;Karen D. Marek

  • Fall Detection in Homes of Older Adults Using the Microsoft Kinect

    Erik E. Stone;Marjorie Skubic

  • Senior residents' perceived need of and preferences for "smart home" sensor technologies.

    George Demiris;Brian K. Hensel;Marjorie Skubic;Marilyn Rantz

  • A smart home application to eldercare: Current status and lessons learned

    Marjorie Skubic;Gregory Alexander;Mihail Popescu;Marilyn Rantz

  • Spatial language for human-robot dialogs

    M. Skubic;D. Perzanowski;S. Blisard;A. Schultz

  • Linguistic summarization of video for fall detection using voxel person and fuzzy logic

    Derek Anderson;Robert H. Luke;James M. Keller;Marjorie Skubic

  • Doppler Radar Fall Activity Detection Using the Wavelet Transform

    Bo Yu Su;K. C. Ho;Marilyn J. Rantz;Marjorie Skubic

  • Needing smart home technologies: the perspectives of older adults in continuing care retirement communities.

    Karen L Courtney;George Demiris;Marilyn Rantz;Marjorie Skubic

  • Recognizing falls from silhouettes.

    Derek Anderson;James M. Keller;Marjorie Skubic;Xi Chen

  • Histogram of oriented normal vectors for object recognition with a depth sensor

    Shuai Tang;Xiaoyu Wang;Xutao Lv;Tony X. Han

  • Automatic fall detection based on Doppler radar motion signature

    Liang Liu;Mihail Popescu;Marjorie Skubic;Marilyn Rantz

  • Unobtrusive, Continuous, In-Home Gait Measurement Using the Microsoft Kinect

    Erik E. Stone;Marjorie Skubic

  • An acoustic fall detector system that uses sound height information to reduce the false alarm rate

    Mihail Popescu;Yun Li;Marjorie Skubic;Marilyn Rantz

  • Passive in-home measurement of stride-to-stride gait variability comparing vision and Kinect sensing

    Erik E. Stone;Marjorie Skubic

  • Evaluation of an inexpensive depth camera for in-home gait assessment

    Erik Stone;Marjorie Skubic

  • Findings from a participatory evaluation of a smart home application for older adults

    George Demiris;Debra Parker Oliver;Geraldine Dickey;Marjorie Skubic

  • A technology and nursing collaboration to help older adults age in place.

    Marilyn J. Rantz;Karen Dorman Marek;Karen Dorman Marek;Myra Aud;Harry W. Tyrer

  • Older adults' privacy considerations for vision based recognition methods of eldercare applications

    George Demiris;Debra Parker Oliver;Jarod Giger;Marjorie Skubic

  • Sensor Technology to Support Aging in Place

    Marilyn J. Rantz;Marjorie Skubic;Steven J. Miller;Colleen Galambos

  • Automated Health Alerts Using In-Home Sensor Data for Embedded Health Assessment

    Marjorie Skubic;Rainer Dane Guevara;Marilyn Rantz

  • Modeling Human Activity From Voxel Person Using Fuzzy Logic

    D. Anderson;R.H. Luke;J.M. Keller;M. Skubic

  • Evaluation of an inexpensive depth camera for passive in-home fall risk assessment

    Erik E. Stone;Marjorie Skubic

Frequent Co-Authors

James M. Keller
James M. Keller University of Missouri
K. C. Ho
K. C. Ho University of Missouri
Alan C. Schultz
Alan C. Schultz United States Naval Research Laboratory
Zhihai He
Zhihai He University of Missouri
J. Gregory Trafton
J. Gregory Trafton United States Naval Research Laboratory
Prasad Calyam
Prasad Calyam University of Missouri
Diane J. Cook
Diane J. Cook Washington State University
Julie A. Adams
Julie A. Adams Oregon State University
Alex Mihailidis
Alex Mihailidis University of Toronto
Jeffrey Kaye
Jeffrey Kaye Oregon Health & Science University

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