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D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Engineering and Technology 37 8258 7958 2280 2112 326 8448

Ming Li publications per year

The chart shows the history of publications by Ming Li between 1992 and 2026, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Ming Li published across 35 years, from 1992 to 2026, averaging 11.5 papers a year. Output peaked at 44 publications in 2025. 45 of the 402 publications appeared in the last two years.

No. of publications
10 20 30 40
Bar chart. Horizontal axis: year, 1992 to 2026. Vertical axis: number of publications, 0 to 44. Peak 44 publications in 2025. 1992: 1 publication 1993: 0 publications 1994: 1 publication 1995: 0 publications 1996: 0 publications 1997: 1 publication 1998: 1 publication 1999: 0 publications 2000: 6 publications 2001: 0 publications 2002: 0 publications 2003: 1 publication 2004: 1 publication 2005: 2 publications 2006: 4 publications 2007: 11 publications 2008: 12 publications 2009: 6 publications 2010: 8 publications 2011: 8 publications 2012: 8 publications 2013: 11 publications 2014: 11 publications 2015: 12 publications 2016: 9 publications 2017: 10 publications 2018: 20 publications 2019: 32 publications 2020: 34 publications 2021: 34 publications 2022: 42 publications 2023: 32 publications 2024: 39 publications 2025: 44 publications 2026: 1 publication
1992 2026

402 publications in total across all disciplines

View publications per year as a table
Ming Li: publications per year, 1992 to 2026
Year Publications
1992 1
1993 0
1994 1
1995 0
1996 0
1997 1
1998 1
1999 0
2000 6
2001 0
2002 0
2003 1
2004 1
2005 2
2006 4
2007 11
2008 12
2009 6
2010 8
2011 8
2012 8
2013 11
2014 11
2015 12
2016 9
2017 10
2018 20
2019 32
2020 34
2021 34
2022 42
2023 32
2024 39
2025 44
2026 1
Total 402
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Ming Li publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Ming Li sits on this spectrum.

No. of scientists
100 200 300 400
Bar chart with 78 bars. Horizontal axis: publications, 38–47 to 804+. Vertical axis: number of scientists, 0 to 457. Most scientists, 457, have 148–157 publications. The last bar groups every scientist with 804 publications or more. The highlighted bar, 318–327 publications, is where this scientist sits. 38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38–47 publications 804+

This scientist: 326 publications — 80th percentile

80% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

View publications distribution as a table
Number of Engineering and Technology scientists by publication count, Research.com 2026 ranking edition. Based on 9,796 ranked scientists.
Publications Scientists This scientist
38–47 20
48–57 35
58–67 96
68–77 135
78–87 190
88–97 259
98–107 283
108–117 369
118–127 341
128–137 386
138–147 372
148–157 457
158–167 415
168–177 407
178–187 421
188–197 378
198–207 403
208–217 317
218–227 346
228–237 321
238–247 260
248–257 280
258–267 240
268–277 214
278–287 242
288–297 203
298–307 166
308–317 154
318–327 175 326
328–337 159
338–347 99
348–357 131
358–367 106
368–377 118
378–387 97
388–397 108
398–407 82
408–417 71
418–427 64
428–437 55
438–447 54
448–457 60
458–467 47
468–477 40
478–487 30
488–497 29
498–507 38
508–517 40
518–527 32
528–537 23
538–547 28
548–557 23
558–567 19
568–577 16
578–587 17
588–597 18
598–607 22
608–617 15
618–627 9
628–637 11
638–647 21
648–657 12
658–667 9
668–677 11
678–687 9
688–697 6
698–707 14
708–717 7
718–727 8
728–737 10
738–747 9
748–757 5
758–767 5
768–777 11
778–787 7
788–797 2
798–803 4
804+ 100
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Ming Li D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Ming Li sits on this spectrum.

No. of scientists
100 200 300 400
Bar chart with 78 bars. Horizontal axis: D-Index, 30 to 107+. Vertical axis: number of scientists, 0 to 426. Most scientists, 426, have 42 D-Index. The last bar groups every scientist with 107 D-Index or more. The highlighted bar, 37 D-Index, is where this scientist sits. 30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 37 D-Index — 16th percentile

16% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

View D-Index distribution as a table
Number of Engineering and Technology scientists by D-index, Research.com 2026 ranking edition. Based on 9,796 ranked scientists.
D-Index Scientists This scientist
30 59
31 114
32 129
33 189
34 200
35 262
36 311
37 312 37
38 350
39 385
40 348
41 362
42 426
43 380
44 310
45 341
46 301
47 306
48 271
49 246
50 210
51 253
52 213
53 221
54 195
55 186
56 170
57 167
58 166
59 144
60 152
61 141
62 138
63 131
64 118
65 114
66 119
67 95
68 87
69 77
70 89
71 69
72 54
73 46
74 55
75 54
76 49
77 53
78 46
79 28
80 39
81 36
82 24
83 26
84 36
85 18
86 25
87 19
88 26
89 27
90 23
91 15
92 12
93 9
94 15
95 10
96 13
97 13
98 9
99 7
100 7
101 8
102 7
103 7
104 9
105 6
106 9
107+ 99
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Overview

Ming Li is a researcher affiliated with The University of Texas at Arlington in the United States. Their work primarily centers on computer science, with a significant focus on signal processing and artificial intelligence. They have contributed extensively to subfields that include computer vision and pattern recognition, cognitive neuroscience, and experimental and cognitive psychology.

Their research topics encompass various aspects of speech and audio technology. Major areas of focus include speech recognition and synthesis, speech and audio processing, and music and audio processing. They also explore natural language processing techniques, topic modeling, emotion and mood recognition, and voice and speech disorders.

Ming Li has published their research in several well-known venues, demonstrating a broad engagement with the academic community. Frequent publication outlets include:

  • arXiv (Cornell University)
  • IEEE/ACM Transactions on Audio Speech and Language Processing
  • SSRN Electronic Journal
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • IEEE Transactions on Affective Computing

Some of their recent publications are:

  • "AISHELL-3: A Multi-speaker Mandarin TTS Corpus and the Baselines" (2020, arXiv)
  • "On-the-Fly Data Loader and Utterance-Level Aggregation for Speaker and Language Recognition" (2020, IEEE/ACM Transactions on Audio Speech and Language Processing)
  • "Simple Attention Module Based Speaker Verification with Iterative Noisy Label Detection" (2022, ICASSP 2022 - IEEE International Conference on Acoustics, Speech and Signal Processing)
  • "Flexible six-dimensional force sensor inspired by the tenon-and-mortise structure of ancient Chinese architecture for orthodontics" (2022, Nano Energy)
  • "STCAM: Spatial-Temporal and Channel Attention Module for Dynamic Facial Expression Recognition" (2020, IEEE Transactions on Affective Computing)

Ming Li often collaborates with a core group of researchers, indicating a network of ongoing partnerships. Their frequent co-authors include:

  • Xiaoyi Qin
  • Danwei Cai
  • Dong Zhang
  • Zexin Cai
  • Weiqing Wang

The breadth of Ming Li's work spans foundational and applied research in speech and audio technologies, with contributions across multiple facets of computer science and related interdisciplinary fields. This profile reflects a body of work characterized by engagement with both theoretical developments and practical implementations in the processing and analysis of auditory and speech-related data.

Best Publications

  • SphereFace: Deep Hypersphere Embedding for Face Recognition

    Weiyang Liu;Yandong Wen;Zhiding Yu;Ming Li

  • A family of oxide ion conductors based on the ferroelectric perovskite Na0.5Bi0.5TiO3

    Ming Li;Martha J. Pietrowski;Roger A. De Souza;Huairuo Zhang

  • A Sensor-Fusion Drivable-Region and Lane-Detection System for Autonomous Vehicle Navigation in Challenging Road Scenarios

    Qingquan Li;Long Chen;Ming Li;Shih-Lung Shaw

  • SphereFace: Deep Hypersphere Embedding for Face Recognition

    Weiyang Liu;Yandong Wen;Zhiding Yu;Ming Li

  • Exploring the Encoding Layer and Loss Function in End-to-End Speaker and Language Recognition System

    Weicheng Cai;Jinkun Chen;Ming Li

  • Soil microbial community and its interaction with soil carbon and nitrogen dynamics following afforestation in central China.

    Qi Deng;Xiaoli Cheng;Dafeng Hui;Qian Zhang

  • Dramatic Influence of A-Site Nonstoichiometry on the Electrical Conductivity and Conduction Mechanisms in the Perovskite Oxide Na0.5Bi0.5TiO3

    Ming Li;Huairuo Zhang;Stuart N. Cook;Linhao Li

  • Identifying children with autism spectrum disorder based on their face processing abnormality: A machine learning framework.

    Wenbo Liu;Ming Li;Li Yi

  • Automatic speaker age and gender recognition using acoustic and prosodic level information fusion

    Ming Li;Kyu J. Han;Shrikanth Narayanan

  • Origin(s) of the apparent high permittivity in CaCu3Ti4O12 ceramics: clarification on the contributions from internal barrier layer capacitor and sample-electrode contact effects

    Ming Li;Zhijian Shen;Mats Nygren;Antonio Feteira

  • Proton Conduction in a Phosphonate-Based Metal-Organic Framework Mediated by Intrinsic "Free Diffusion inside a Sphere".

    Simona Pili;Stephen P. Argent;Christopher G. Morris;Peter Rought

  • End-to-End Open-Domain Question Answering with BERTserini

    Wei Yang;Yuqing Xie;Aileen Lin;Xingyu Li

  • A Novel Coordination Polymer as Positive Electrode Material for Lithium Ion Battery

    Jiangfeng Xiang;Caixian Chang;Ming Li;Simin Wu

  • Defect chemistry and electrical properties of sodium bismuth titanate perovskite

    F. Yang;M. Li;L. Li;P. Wu

  • Multimodal Physical Activity Recognition by Fusing Temporal and Cepstral Information

    Ming Li;Viktor Rozgić;Gautam Thatte;Sangwon Lee

  • Syntheses, Structures, and Photoluminescence of Three Novel Coordination Polymers Constructed from Dimeric d10 Metal Units

    Ming Li;Jiangfeng Xiang;Liangjie Yuan;Simin Wu

  • Bismuth Sodium Titanate Based Materials for Piezoelectric Actuators

    Klaus Reichmann;Antonio Feteira;Ming Li

  • Bubble-supported engineering of hierarchical CuCo2S4 hollow spheres for enhanced electrochemical performance

    Huihui You;Lei Zhang;Yinzhu Jiang;Tianyan Shao

  • The impact of agricultural land use changes on soil organic carbon dynamics in the Danjiangkou Reservoir area of China

    Xiaoli Cheng;Yuanhe Yang;Ming Li;Xiaolin Dou

  • RWF-2000: An Open Large Scale Video Database for Violence Detection

    Ming Cheng;Kunjing Cai;Ming Li

  • Relaxor ferroelectric-like high effective permittivity in leaky dielectrics/oxide semiconductors induced by electrode effects: A case study of CuO ceramics

    Ming Li;Antonio Feteira;Derek C. Sinclair

  • LSTM based Similarity Measurement with Spectral Clustering for Speaker Diarization

    Qingjian Lin;Ruiqing Yin;Ming Li;Hervé Bredin

  • Facial Expression Recognition with Identity and Emotion Joint Learning

    Ming Li;Hao Xu;Xingchang Huang;Zhanmei Song

  • Automatic intelligibility classification of sentence-level pathological speech.

    Jangwon Kim;Naveen Kumar;Andreas Tsiartas;Ming Li

  • Opportunistic broadcast of event-driven warning messages in Vehicular Ad Hoc Networks with lossy links

    Ming Li;Kai Zeng;Wenjing Lou

  • Incremental local online Gaussian Mixture Regression for imitation learning of multiple tasks

    Thomas Cederborg;Ming Li;Adrien Baranes;Pierre-Yves Oudeyer

  • String Stability Analysis for Vehicle Platooning Under Unreliable Communication Links With Event-Triggered Strategy

    Zhicheng Li;Bin Hu;Ming Li;Gengnan Luo

  • An open-source 3D solar radiation model integrated with a 3D Geographic Information System

    Jianming Liang;Jianhua Gong;Jieping Zhou;Abdoul Nasser Ibrahim

  • A Novel Learnable Dictionary Encoding Layer for End-to-End Language Identification

    Weicheng Cai;Zexin Cai;Xiang Zhang;Xiaoqi Wang

  • AISHELL-3: A Multi-speaker Mandarin TTS Corpus and the Baselines.

    Yao Shi;Hui Bu;Xin Xu;Shaoji Zhang

  • Countermeasures for Automatic Speaker Verification Replay Spoofing Attack : On Data Augmentation, Feature Representation, Classification and Fusion.

    Weicheng Cai;Danwei Cai;Wenbo Liu;Gang Li

  • Simplified supervised i-vector modeling with application to robust and efficient language identification and speaker verification

    Ming Li;Ming Li;Shrikanth S. Narayanan

  • A data trust framework for VANETs enabling false data detection and secure vehicle tracking

    Mingshun Sun;Ming Li;Ryan Gerdes

  • SIMPLE: single-frame based physical layer identification for intrusion detection and prevention on in-vehicle networks

    Mahsa Foruhandeh;Yanmao Man;Ryan Gerdes;Ming Li

  • The DKU Replay Detection System for the ASVspoof 2019 Challenge: On Data Augmentation, Feature Representation, Classification, and Fusion

    Weicheng Cai;Haiwei Wu;Danwei Cai;Ming Li

  • On-the-Fly Data Loader and Utterance-Level Aggregation for Speaker and Language Recognition

    Weicheng Cai;Jinkun Chen;Jun Zhang;Ming Li

Frequent Co-Authors

Shrikanth S. Narayanan
Shrikanth S. Narayanan University of Southern California
Derek C. Sinclair
Derek C. Sinclair University of Sheffield
Hai Wang
Hai Wang Stanford University
Murali Annavaram
Murali Annavaram University of Southern California
Urbashi Mitra
Urbashi Mitra University of Southern California
Hui Shen
Hui Shen Sun Yat-sen University
Donna Spruijt-Metz
Donna Spruijt-Metz University of Southern California
Zhijian Pei
Zhijian Pei Texas A&M University
Antonio Feteira
Antonio Feteira Sheffield Hallam University
John B. Claridge
John B. Claridge University of Liverpool

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