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Mingxia Liu

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 53 4894 4759 2274 2195 153 9431

Mingxia Liu publications per year

The chart shows the history of publications by Mingxia Liu between 2008 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Mingxia Liu published across 18 years, from 2008 to 2025, averaging 17.6 papers a year. Output peaked at 45 publications in 2023. 82 of the 316 publications appeared in the last two years.

No. of publications
10 20 30 40
Bar chart. Horizontal axis: year, 2008 to 2025. Vertical axis: number of publications, 0 to 45. Peak 45 publications in 2023. 2008: 1 publication 2009: 3 publications 2010: 3 publications 2011: 1 publication 2012: 3 publications 2013: 1 publication 2014: 3 publications 2015: 7 publications 2016: 11 publications 2017: 13 publications 2018: 18 publications 2019: 22 publications 2020: 33 publications 2021: 27 publications 2022: 43 publications 2023: 45 publications 2024: 45 publications 2025: 37 publications
2008 2025

316 publications in total across all disciplines

View publications per year as a table
Mingxia Liu: publications per year, 2008 to 2025
Year Publications
2008 1
2009 3
2010 3
2011 1
2012 3
2013 1
2014 3
2015 7
2016 11
2017 13
2018 18
2019 22
2020 33
2021 27
2022 43
2023 45
2024 45
2025 37
Total 316
Download as CSV

Mingxia Liu 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 Mingxia Liu 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, 152–161 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: 153 publications — 28th percentile

28% 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
152–161 559 153
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
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
Download as CSV

Mingxia Liu 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 Mingxia Liu 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, 52–53 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: 53 D-Index — 67th percentile

67% 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 53
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
Download as CSV

Overview

Mingxia Liu is affiliated with the University of North Carolina at Chapel Hill in the United States. Their research primarily focuses on applications within medicine and neuroscience, with significant contributions intersecting cognitive neuroscience, radiology, nuclear medicine and imaging, artificial intelligence, computer vision and pattern recognition, and neurology.

The scientist's work covers several specialized topics, including functional brain connectivity studies, advanced MRI techniques and applications, advanced neuroimaging techniques and applications, EEG and brain-computer interfaces, brain tumor detection and classification, radiomics and machine learning in medical imaging, as well as domain adaptation and few-shot learning.

Recent publications by Mingxia Liu include:

  • Federated learning for medical image analysis: A survey, 2024, published in Pattern Recognition
  • A Survey on Deep Learning for Neuroimaging-Based Brain Disorder Analysis, 2020, published in Frontiers in Neuroscience
  • A Mutual Multi-Scale Triplet Graph Convolutional Network for Classification of Brain Disorders Using Functional or Structural Connectivity, 2021, published in IEEE Transactions on Medical Imaging
  • Multi-site MRI harmonization via attention-guided deep domain adaptation for brain disorder identification, 2021, published in Medical Image Analysis
  • Disease-Image-Specific Learning for Diagnosis-Oriented Neuroimage Synthesis With Incomplete Multi-Modality Data, 2021, published in IEEE Transactions on Pattern Analysis and Machine Intelligence

Mingxia Liu frequently collaborates with a group of coauthors, including Dinggang Shen, Pew-Thian Yap, Lishan Qiao, Daoqiang Zhang, and Yuqi Fang.

Their publications have appeared predominantly in venues such as:

  • UNC Libraries
  • arXiv (Cornell University)
  • Medical Image Analysis
  • Lecture Notes in Computer Science
  • SSRN Electronic Journal

Best Publications

  • Domain Adaptation for Medical Image Analysis: A Survey

    Hao Guan;Mingxia Liu

  • Hierarchical Fully Convolutional Network for Joint Atrophy Localization and Alzheimer's Disease Diagnosis Using Structural MRI

    Chunfeng Lian;Mingxia Liu;Jun Zhang;Dinggang Shen

  • Landmark-based deep multi-instance learning for brain disease diagnosis

    Mingxia Liu;Jun Zhang;Ehsan Adeli;Dinggang Shen;Dinggang Shen

  • Joint Classification and Regression via Deep Multi-Task Multi-Channel Learning for Alzheimer's Disease Diagnosis

    Mingxia Liu;Jun Zhang;Ehsan Adeli;Dinggang Shen

  • A Survey on Deep Learning for Neuroimaging-Based Brain Disorder Analysis.

    Li Zhang;Li Zhang;Mingliang Wang;Mingxia Liu;Daoqiang Zhang

  • Relationship Induced Multi-Template Learning for Diagnosis of Alzheimer’s Disease and Mild Cognitive Impairment

    Mingxia Liu;Daoqiang Zhang;Dinggang Shen

  • Latent Representation Learning for Alzheimer’s Disease Diagnosis With Incomplete Multi-Modality Neuroimaging and Genetic Data

    Tao Zhou;Mingxia Liu;Kim-Han Thung;Dinggang Shen

  • Domain Transfer Learning for MCI Conversion Prediction

    Bo Cheng;Mingxia Liu;Daoqiang Zhang;Brent C. Munsell

  • Detecting Anatomical Landmarks From Limited Medical Imaging Data Using Two-Stage Task-Oriented Deep Neural Networks

    Jun Zhang;Mingxia Liu;Dinggang Shen

  • Synthesizing Missing PET from MRI with Cycle-consistent Generative Adversarial Networks for Alzheimer's Disease Diagnosis.

    Yongsheng Pan;Mingxia Liu;Chunfeng Lian;Tao Zhou

  • Alzheimer's Disease Diagnosis Using Landmark-Based Features From Longitudinal Structural MR Images.

    Jun Zhang;Mingxia Liu;Le An;Yaozong Gao

  • Integration of temporal and spatial properties of dynamic connectivity networks for automatic diagnosis of brain disease

    Biao Jie;Biao Jie;Mingxia Liu;Dinggang Shen;Dinggang Shen

  • Inherent Structure-Based Multiview Learning With Multitemplate Feature Representation for Alzheimer's Disease Diagnosis

    Mingxia Liu;Daoqiang Zhang;Ehsan Adeli;Dinggang Shen

  • Anatomical Landmark Based Deep Feature Representation for MR Images in Brain Disease Diagnosis

    Mingxia Liu;Jun Zhang;Dong Nie;Pew-Thian Yap

  • Identifying Autism Spectrum Disorder With Multi-Site fMRI via Low-Rank Domain Adaptation

    Mingliang Wang;Daoqiang Zhang;Jiashuang Huang;Pew-Thian Yap

  • A Mutual Multi-Scale Triplet Graph Convolutional Network for Classification of Brain Disorders Using Functional or Structural Connectivity

    Dongren Yao;Jing Sui;Mingliang Wang;Erkun Yang

  • NLH: A Blind Pixel-Level Non-Local Method for Real-World Image Denoising

    Yingkun Hou;Jun Xu;Mingxia Liu;Guanghai Liu

  • View-aligned hypergraph learning for Alzheimer's disease diagnosis with incomplete multi-modality data

    Mingxia Liu;Jun Zhang;Pew Thian Yap;Dinggang Shen;Dinggang Shen

  • Two-Stage Cost-Sensitive Learning for Software Defect Prediction

    Mingxia Liu;Linsong Miao;Daoqiang Zhang

  • Spatial-Temporal Dependency Modeling and Network Hub Detection for Functional MRI Analysis via Convolutional-Recurrent Network

    Mingliang Wang;Chunfeng Lian;Dongren Yao;Daoqiang Zhang

  • Strength and Similarity Guided Group-level Brain Functional Network Construction for MCI Diagnosis.

    Yu Zhang;Yu Zhang;Han Zhang;Xiaobo Chen;Mingxia Liu

  • Multi-channel multi-scale fully convolutional network for 3D perivascular spaces segmentation in 7T MR images.

    Chunfeng Lian;Jun Zhang;Mingxia Liu;Xiaopeng Zong

  • View‐centralized multi‐atlas classification for Alzheimer's disease diagnosis

    Mingxia Liu;Daoqiang Zhang;Dinggang Shen;Alzheimer's Disease Neuroimaging Initiative

Frequent Co-Authors

Dinggang Shen
Dinggang Shen ShanghaiTech University
Daoqiang Zhang
Daoqiang Zhang Nanjing University of Aeronautics and Astronautics
Pew Thian Yap
Pew Thian Yap University of North Carolina at Chapel Hill
Weili Lin
Weili Lin University of North Carolina at Chapel Hill
Ehsan Adeli
Ehsan Adeli Stanford University
Feng Shi
Feng Shi United Imaging Intelligence (China)
Yong Xia
Yong Xia Northwestern Polytechnical University
Jing Sui
Jing Sui Beijing Normal University
Han Zhang
Han Zhang ShanghaiTech University
Songcan Chen
Songcan Chen Nanjing University of Aeronautics and Astronautics

External Links

Personal website of Mingxia Liu Google Scholar page

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Best Scientists Citing Mingxia Liu

Dinggang Shen

Dinggang Shen

ShanghaiTech University

Publications: 137

Weili Lin

Weili Lin

University of North Carolina at Chapel Hill

Publications: 39

Daoqiang Zhang

Daoqiang Zhang

Nanjing University of Aeronautics and Astronautics

Publications: 38

Baiying Lei

Baiying Lei

Shenzhen University

Publications: 33

Gang Li

Gang Li

University of North Carolina at Chapel Hill

Publications: 30

Pew Thian Yap

Pew Thian Yap

University of North Carolina at Chapel Hill

Publications: 27

Han Zhang

Han Zhang

ShanghaiTech University

Publications: 21

Ehsan Adeli

Ehsan Adeli

Stanford University

Publications: 20

Vince D. Calhoun

Vince D. Calhoun

Georgia State University

Publications: 19

Tianfu Wang

Tianfu Wang

Shenzhen University

Publications: 19

Feng Shi

Feng Shi

United Imaging Intelligence (China)

Publications: 17

U. Rajendra Acharya

U. Rajendra Acharya

University of Southern Queensland

Publications: 13

Jing Sui

Jing Sui

Beijing Normal University

Publications: 12

Qian Wang

Qian Wang

Shanghai Jiao Tong University

Publications: 12

Ling Shao

Ling Shao

Terminus International

Publications: 12

Daniel Rueckert

Daniel Rueckert

Technical University of Munich

Publications: 12

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