Ming Lei

2.0k total citations · 1 hit paper
50 papers, 1.3k citations indexed

About

Ming Lei is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Ming Lei has authored 50 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Artificial Intelligence, 21 papers in Signal Processing and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Ming Lei's work include Speech Recognition and Synthesis (28 papers), Speech and Audio Processing (18 papers) and Music and Audio Processing (17 papers). Ming Lei is often cited by papers focused on Speech Recognition and Synthesis (28 papers), Speech and Audio Processing (18 papers) and Music and Audio Processing (17 papers). Ming Lei collaborates with scholars based in China, United States and Cayman Islands. Ming Lei's co-authors include Hui‐Xiong Deng, Jing Wei, Xiangyu Sun, Xuan Chu, Ji-Gen Chen, Kun Xu, Zhongming Wei, Shiliang Zhang, Li-Rong Dai and Zhijie Yan and has published in prestigious journals such as IEEE Access, Technological Forecasting and Social Change and Neurocomputing.

In The Last Decade

Ming Lei

49 papers receiving 1.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Machine learning in materials science

2019 707 citations Jing Wei, Xuan Chu et al. InfoMat profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Ming Lei China	14	427	408	238	196	153	50	1.3k
Xu Yang China	20	124 0.3×	294 0.7×	64 0.3×	334 1.7×	228 1.5×	98	1.4k
Brian S. Mitchell United States	22	587 1.4×	893 2.2×	72 0.3×	191 1.0×	197 1.3×	73	2.8k
Zhiguo Zhou China	19	201 0.5×	298 0.7×	42 0.2×	202 1.0×	137 0.9×	86	1.3k
Yang Guo China	22	148 0.3×	212 0.5×	125 0.5×	341 1.7×	89 0.6×	127	2.1k
Jianhua Jiang China	26	702 1.6×	487 1.2×	66 0.3×	386 2.0×	406 2.7×	163	2.3k
Jun Yin China	20	196 0.5×	164 0.4×	128 0.5×	116 0.6×	168 1.1×	72	1.3k
Zhongjie Wang China	16	185 0.4×	167 0.4×	34 0.1×	201 1.0×	106 0.7×	100	1.0k
Amit Chakrabarti United States	22	142 0.3×	450 1.1×	82 0.3×	235 1.2×	86 0.6×	70	1.6k
Sunil Gupta Australia	18	154 0.4×	286 0.7×	30 0.1×	112 0.6×	187 1.2×	70	1.2k
Jing Jiang China	26	148 0.3×	223 0.5×	82 0.3×	1.3k 6.5×	98 0.6×	143	2.1k

Countries citing papers authored by Ming Lei

Since Specialization

Citations

This map shows the geographic impact of Ming Lei's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ming Lei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Lei more than expected).

Fields of papers citing papers by Ming Lei

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ming Lei. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ming Lei. The network helps show where Ming Lei may publish in the future.

Co-authorship network of co-authors of Ming Lei

This figure shows the co-authorship network connecting the top 25 collaborators of Ming Lei. A scholar is included among the top collaborators of Ming Lei based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ming Lei. Ming Lei is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Yao, Yiwu, et al.. (2021). Extremely Low Footprint End-to-End ASR System for Smart Device. Figshare. 4548–4552. 6 indexed citations

2.

Zhang, Shiliang, et al.. (2021). Investigation of Spatial-Acoustic Features for Overlapping Speech Detection in Multiparty Meetings. 3550–3554. 4 indexed citations

3.

Zhu, Donghua, et al.. (2021). R&D trend analysis based on patent mining: An integrated use of patent applications and invalidation data. Technological Forecasting and Social Change. 167. 120691–120691. 34 indexed citations

4.

Du, Zhihao, Ming Lei, Jiqing Han, & Shiliang Zhang. (2020). Pan: Phoneme-Aware Network for Monaural Speech Enhancement. 6634–6638. 2 indexed citations

5.

Zhang, Shiliang, et al.. (2020). Streaming Chunk-Aware Multihead Attention for Online End-to-End Speech Recognition. 2142–2146. 9 indexed citations

6.

Li, Wei, Sicheng Wang, Ming Lei, Sabato Marco Siniscalchi, & Chin‐Hui Lee. (2019). Improving Audio-visual Speech Recognition Performance with Cross-modal Student-teacher Training. Nova Science Publishers (Nova Science Publishers, Inc.). 6560–6564. 13 indexed citations

7.

Wei, Jing, Xuan Chu, Xiangyu Sun, et al.. (2019). Machine learning in materials science. InfoMat. 1(3). 338–358. 707 indexed citations breakdown →

8.

Zhang, Shiliang, Yuan Liu, Ming Lei, Bin Ma, & Lei Xie. (2019). Towards Language-Universal Mandarin-English Speech Recognition. 2170–2174. 10 indexed citations

9.

Zhang, Shiliang, Ming Lei, & Zhijie Yan. (2019). Investigation of Transformer Based Spelling Correction Model for CTC-Based End-to-End Mandarin Speech Recognition. 2180–2184. 16 indexed citations

10.

Zhang, Shiliang, et al.. (2018). Compact Feedforward Sequential Memory Networks for Small-footprint Keyword Spotting. 2663–2667. 8 indexed citations

11.

Zhang, Shiliang & Ming Lei. (2018). Acoustic Modeling with DFSMN-CTC and Joint CTC-CE Learning. 771–775. 6 indexed citations

12.

Yuan, Yuan & Ming Lei. (2017). The Negative Effect of Brand Attachment: How Attachment Styles Help Explain Anti-Brand Behavior. Open Journal of Business and Management. 5(1). 141–148. 5 indexed citations

13.

Lei, Ming, Yao Qian, Frank K. Soong, et al.. (2015). Modeling F0 trajectories in hierarchically structured deep neural networks. Speech Communication. 76. 82–92. 14 indexed citations

14.

Lei, Ming, Yao Qian, Frank K. Soong, et al.. (2014). Modeling DCT parameterized F0 trajectory at intonation phrase level with DNN or decision tree. 2273–2277. 7 indexed citations

15.

Lei, Ming, et al.. (2013). An Empirical Study on Usage Intention of Mobile E-Commerce: Technology Acceptance Model Approach. 9. 552–554. 2 indexed citations

16.

Lei, Ming, Zhongliang Jing, & Shiqiang Hu. (2012). Scaled unscented transform-based variational optimality filter. 487–494.

17.

Lei, Ming, Zhen-Hua Ling, & Li-Rong Dai. (2011). Preserve ordering property of generated LSPS for minimum generation error training in HMM-based speech synthesis. 4712–4715. 2 indexed citations

18.

Jiang, Yuan, Zhen-Hua Ling, Ming Lei, et al.. (2010). The USTC System for Blizzard Challenge 2010. 115–120. 4 indexed citations

19.

Lu, Heng, Zhen-Hua Ling, Ming Lei, et al.. (2009). The USTC System for Blizzard Challenge 2009. 101–106. 7 indexed citations

20.

Lei, Ming. (2008). Image completion by exemplar patch. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact