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Computer Science
Australia
2026

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 139 71 68 2 2 651 77251

U. Rajendra Acharya publications per year

The chart shows the history of publications by U. Rajendra Acharya between 1997 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. U. Rajendra Acharya published across 29 years, from 1997 to 2025, averaging 34 papers a year. Output peaked at 129 publications in 2023. 144 of the 985 publications appeared in the last two years.

No. of publications
25 50 75 100 125
Bar chart. Horizontal axis: year, 1997 to 2025. Vertical axis: number of publications, 0 to 129. Peak 129 publications in 2023. 1997: 1 publication 1998: 0 publications 1999: 1 publication 2000: 0 publications 2001: 1 publication 2002: 2 publications 2003: 3 publications 2004: 4 publications 2005: 8 publications 2006: 7 publications 2007: 9 publications 2008: 5 publications 2009: 6 publications 2010: 11 publications 2011: 34 publications 2012: 46 publications 2013: 61 publications 2014: 31 publications 2015: 29 publications 2016: 29 publications 2017: 44 publications 2018: 51 publications 2019: 59 publications 2020: 63 publications 2021: 104 publications 2022: 103 publications 2023: 129 publications 2024: 84 publications 2025: 60 publications
1997 2025

985 publications in total across all disciplines

View publications per year as a table
U. Rajendra Acharya: publications per year, 1997 to 2025
Year Publications
1997 1
1998 0
1999 1
2000 0
2001 1
2002 2
2003 3
2004 4
2005 8
2006 7
2007 9
2008 5
2009 6
2010 11
2011 34
2012 46
2013 61
2014 31
2015 29
2016 29
2017 44
2018 51
2019 59
2020 63
2021 104
2022 103
2023 129
2024 84
2025 60
Total 985
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U. Rajendra Acharya 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 U. Rajendra Acharya sits on this spectrum.

No. of scientists
200 400 600
Bar chart with 97 bars. Horizontal axis: publications, 32–41 to 991+. Vertical axis: number of scientists, 0 to 609. Most scientists, 609, have 142–151 publications. The last bar groups every scientist with 991 publications or more. The highlighted bar, 642–651 publications, is where this scientist sits. 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
32–41 publications 991+

This scientist: 651 publications — 97th percentile

97% of scientists in this discipline score the same or lower.

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

View publications distribution as a table
Number of Computer Science scientists by publication count, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
Publications Scientists This scientist
32–41 7
42–51 22
52–61 82
62–71 134
72–81 249
82–91 324
92–101 421
102–111 420
112–121 497
122–131 544
132–141 555
142–151 609
152–161 559
162–171 534
172–181 556
182–191 583
192–201 519
202–211 508
212–221 490
222–231 437
232–241 423
242–251 408
252–261 377
262–271 301
272–281 335
282–291 320
292–301 293
302–311 250
312–321 238
322–331 206
332–341 209
342–351 208
352–361 162
362–371 176
372–381 127
382–391 158
392–401 128
402–411 104
412–421 94
422–431 99
432–441 83
442–451 108
452–461 73
462–471 77
472–481 69
482–491 84
492–501 62
502–511 54
512–521 57
522–531 51
532–541 51
542–551 32
552–561 38
562–571 28
572–581 43
582–591 33
592–601 41
602–611 32
612–621 28
622–631 25
632–641 27
642–651 17 651
652–661 20
662–671 17
672–681 15
682–691 14
692–701 21
702–711 13
712–721 12
722–731 19
732–741 14
742–751 12
752–761 10
762–771 10
772–781 11
782–791 10
792–801 11
802–811 8
812–821 8
822–831 7
832–841 11
842–851 10
852–861 5
862–871 9
872–881 4
882–891 6
892–901 3
902–911 6
912–921 3
922–931 2
932–941 2
942–951 2
952–961 3
962–971 3
972–981 3
982–990 5
991+ 100
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U. Rajendra Acharya 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 U. Rajendra Acharya sits on this spectrum.

No. of scientists
200 400 600 800
Bar chart with 52 bars. Horizontal axis: D-Index, 30–31 to 131+. Vertical axis: number of scientists, 0 to 990. Most scientists, 990, have 36–37 D-Index. The last bar groups every scientist with 131 D-Index or more. The highlighted bar, 131+ D-Index, is where this scientist sits. 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
30–31 D-Index 131+

This scientist: 139 D-Index — 100th percentile

100% of scientists in this discipline score the same or lower.

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

View D-Index distribution as a table
Number of Computer Science scientists by D-index, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
D-Index Scientists This scientist
30–31 879
32–33 983
34–35 918
36–37 990
38–39 968
40–41 907
42–43 821
44–45 763
46–47 689
48–49 543
50–51 543
52–53 518
54–55 500
56–57 458
58–59 400
60–61 337
62–63 308
64–65 292
66–67 249
68–69 213
70–71 192
72–73 189
74–75 165
76–77 139
78–79 119
80–81 121
82–83 113
84–85 88
86–87 87
88–89 75
90–91 69
92–93 57
94–95 46
96–97 38
98–99 34
100–101 36
102–103 27
104–105 37
106–107 18
108–109 31
110–111 19
112–113 16
114–115 12
116–117 20
118–119 15
120–121 5
122–123 20
124–125 8
126–127 5
128–129 7
130 3
131+ 98 139
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Research.com Recognitions

  • 2026 - Research.com Computer Science in Australia Leader Award
  • 2025 - Research.com Computer Science in Australia Leader Award
  • 2022 - Research.com Computer Science in Australia Leader Award

Overview

U. Rajendra Acharya is affiliated with the University of Southern Queensland in Australia. Their research spans multiple fields including Medicine, Computer Science, and Neuroscience, with a notable focus on interdisciplinary applications of technology in healthcare.

The main areas of study for Acharya include Medicine with 573 publications, Computer Science with 287 publications, and Neuroscience with 275 publications. Within these fields, the subfields of Cognitive Neuroscience, Artificial Intelligence, Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging, and Biomedical Engineering represent significant domains of their work.

The scientist's research topics cover a range of applications, particularly in biomedical signal processing and artificial intelligence. Their principal topics include:

  • EEG and Brain-Computer Interfaces
  • ECG Monitoring and Analysis
  • AI in cancer detection
  • COVID-19 diagnosis using AI
  • Radiomics and Machine Learning in Medical Imaging
  • Functional Brain Connectivity Studies
  • Non-Invasive Vital Sign Monitoring

Acharya has published extensively in prominent venues, with frequent contributions to:

  • Computers in Biology and Medicine (57 publications)
  • arXiv (Cornell University) (33 publications)
  • IEEE Access (32 publications)
  • Computer Methods and Programs in Biomedicine (31 publications)
  • International Journal of Environmental Research and Public Health (17 publications)

Their recent papers illustrate a strong emphasis on the application of deep learning and artificial intelligence in medical diagnostics and imaging:

  • "Automated detection of COVID-19 cases using deep neural networks with X-ray images" (2020), Computers in Biology and Medicine
  • "A review of uncertainty quantification in deep learning: Techniques, applications and challenges" (2021), Information Fusion
  • "Application of deep learning technique to manage COVID-19 in routine clinical practice using CT images: Results of 10 convolutional neural networks" (2020), Computers in Biology and Medicine
  • "ABCDM: An Attention-based Bidirectional CNN-RNN Deep Model for sentiment analysis" (2020), Future Generation Computer Systems
  • "Application of explainable artificial intelligence for healthcare: A systematic review of the last decade (2011-2022)" (2022), Computer Methods and Programs in Biomedicine

The scientist frequently collaborates with several researchers, including:

  • Prabal Datta Barua
  • Ru-San Tan
  • Şengül Doğan
  • Türker Tuncer
  • Mehmet Bayğın

In addition to journal articles, Acharya has contributed to book publications, notably with Springer Science+Business Media, including the titled work "Proceedings of International Conference on Communication, Circuits, and Systems" published in 2021.

Best Publications

  • Heart rate variability: a review

    U. Rajendra Acharya;K. Paul Joseph;N. Kannathal;Choo Min Lim

  • Automated detection of COVID-19 cases using deep neural networks with X-ray images.

    Tulin Ozturk;Muhammed Talo;Eylul Azra Yildirim;Ulas Baran Baloglu

  • A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges

    Moloud Abdar;Farhad Pourpanah;Sadiq Hussain;Dana Rezazadegan

  • Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals.

    U. Rajendra Acharya;U. Rajendra Acharya;U. Rajendra Acharya;Shu Lih Oh;Yuki Hagiwara;Jen Hong Tan

  • A deep convolutional neural network model to classify heartbeats

    U. Rajendra Acharya;Shu Lih Oh;Yuki Hagiwara;Jen Hong Tan

  • Deep learning for healthcare applications based on physiological signals: A review.

    Oliver Faust;Yuki Hagiwara;Tan Jen Hong;Oh Shu Lih

  • Entropies for detection of epilepsy in EEG

    N. Kannathal;Min Lim Choo;U. Rajendra Acharya;P. K. Sadasivan

  • Application of deep convolutional neural network for automated detection of myocardial infarction using ECG signals

    U. Rajendra Acharya;U. Rajendra Acharya;U. Rajendra Acharya;Hamido Fujita;Shu Lih Oh;Yuki Hagiwara

  • Automated EEG analysis of epilepsy: A review

    U. Rajendra Acharya;S. Vinitha Sree;G. Swapna;Roshan Joy Martis

  • Arrhythmia detection using deep convolutional neural network with long duration ECG signals.

    Özal Yildirim;Pawel Plawiak;Ru San Tan;U. Rajendra Acharya

  • Application of deep learning technique to manage COVID-19 in routine clinical practice using CT images: Results of 10 convolutional neural networks.

    Ali Abbasian Ardakani;Alireza Rajabzadeh Kanafi;U. Rajendra Acharya;Nazanin Khadem

  • ECG beat classification using PCA, LDA, ICA and Discrete Wavelet Transform

    Roshan Joy Martis;U. Rajendra Acharya;U. Rajendra Acharya;Lim Choo Min

  • Automated detection of arrhythmias using different intervals of tachycardia ECG segments with convolutional neural network

    U. Rajendra Acharya;Hamido Fujita;Oh Shu Lih;Yuki Hagiwara

  • Automated diagnosis of epileptic EEG using entropies

    U. Rajendra Acharya;Filippo Molinari;S. Vinitha Sree;Subhagata Chattopadhyay

  • Automated diagnosis of arrhythmia using combination of CNN and LSTM techniques with variable length heart beats

    Shu Lih Oh;Eddie Yin Kwee Ng;Ru San Tan;U. Rajendra Acharya

  • ABCDM: An Attention-based Bidirectional CNN-RNN Deep Model for sentiment analysis

    Mohammad Ehsan Basiri;Shahla Nemati;Moloud Abdar;Erik Cambria

  • Automated EEG-based screening of depression using deep convolutional neural network.

    U. Rajendra Acharya;U. Rajendra Acharya;U. Rajendra Acharya;Shu Lih Oh;Yuki Hagiwara;Jen Hong Tan

  • A deep learning approach for Parkinson’s disease diagnosis from EEG signals

    Shu Lih Oh;Yuki Hagiwara;U. Raghavendra;Rajamanickam Yuvaraj

  • Wavelet-based EEG processing for computer-aided seizure detection and epilepsy diagnosis.

    Oliver Faust;U. Rajendra Acharya;Hojjat Adeli;Amir Adeli

  • Non-linear analysis of EEG signals at various sleep stages

    U Rajendra Acharya;Oliver Faust;N. Kannathal;TjiLeng Chua

  • Computer-aided diagnosis of diabetic retinopathy: A review

    Muthu Rama Krishnan Mookiah;U. Rajendra Acharya;U. Rajendra Acharya;Chua Kuang Chua;Choo Min Lim

Frequent Co-Authors

Jasjit S. Suri
Jasjit S. Suri University of Idaho
Jen Hong Tan
Jen Hong Tan Singapore General Hospital
Filippo Molinari
Filippo Molinari Polytechnic University of Turin
Oliver Faust
Oliver Faust Sheffield Hallam University
S. Vinitha Sree
S. Vinitha Sree Nanyang Technological University
Hamido Fujita
Hamido Fujita University of Technology Malaysia
Shu Lih Oh
Shu Lih Oh Ngee Ann Polytechnic
Eddie Y. K. Ng
Eddie Y. K. Ng Nanyang Technological University
Joel En Wei Koh
Joel En Wei Koh Ngee Ann Polytechnic
Andrew N. Nicolaides
Andrew N. Nicolaides Imperial College London

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