M. Mao

5.0k total citations · 3 hit papers
18 papers, 2.6k citations indexed

About

M. Mao is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, M. Mao has authored 18 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 4 papers in Signal Processing. Recurrent topics in M. Mao's work include Speech Recognition and Synthesis (7 papers), Speech and Audio Processing (4 papers) and Music and Audio Processing (3 papers). M. Mao is often cited by papers focused on Speech Recognition and Synthesis (7 papers), Speech and Audio Processing (4 papers) and Music and Audio Processing (3 papers). M. Mao collaborates with scholars based in United States, Canada and Australia. M. Mao's co-authors include Andrew Senior, Rajat Monga, Jay B. Dean, Ke Yang, Quoc V. Le, Vincent Vanhoucke, Greg S. Corrado, Matthieu Devin, Paul A. Tucker and Marc’Aurelio Ranzato and has published in prestigious journals such as Nucleic Acids Research, Blood and IEEE Transactions on Information Theory.

In The Last Decade

M. Mao

15 papers receiving 2.5k citations

Hit Papers

Large Scale Distributed Deep Networks 2011 2026 2016 2021 2012 2011 2013 500 1000 1.5k
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.

  1. Large Scale Distributed Deep Networks
    2012 1.7k citations Jay B. Dean, Greg S. Corrado et al. Neural Information Processing Systems profile →
  2. Improving the speed of neural networks on CPUs
    2011 384 citations Vincent Vanhoucke, Andrew Senior et al. profile →
  3. On rectified linear units for speech processing
    2013 315 citations Matthew D. Zeiler, Rajat Monga et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
M. Mao United States 7 1.6k 1.1k 421 393 322 18 2.6k
Matthieu Devin United States 5 1.6k 1.0× 959 0.9× 383 0.9× 382 1.0× 255 0.8× 6 2.4k
Li Deng China 14 2.0k 1.2× 964 0.9× 414 1.0× 255 0.6× 606 1.9× 43 3.3k
Rajat Monga United States 6 2.3k 1.4× 2.2k 2.1× 486 1.2× 414 1.1× 318 1.0× 8 4.0k
Ke Yang China 14 1.9k 1.2× 1.2k 1.2× 661 1.6× 863 2.2× 264 0.8× 62 3.4k
Qiang Liu China 26 1.4k 0.9× 869 0.8× 390 0.9× 617 1.6× 192 0.6× 164 2.8k
豊 松尾 3 1.7k 1.1× 1.5k 1.4× 296 0.7× 167 0.4× 277 0.9× 5 3.6k
Shu‐Tao Xia China 32 2.0k 1.2× 2.4k 2.3× 501 1.2× 1.0k 2.6× 358 1.1× 284 5.0k
Guillaume Desjardins Canada 11 3.3k 2.0× 2.0k 1.9× 339 0.8× 213 0.5× 359 1.1× 29 4.8k
Patrice Simard United States 25 1.5k 0.9× 1.4k 1.3× 339 0.8× 101 0.3× 198 0.6× 35 3.1k
Bo Li China 27 1.3k 0.8× 771 0.7× 553 1.3× 1.2k 3.0× 728 2.3× 224 3.8k

Countries citing papers authored by M. Mao

Since Specialization
Citations

This map shows the geographic impact of M. Mao'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 M. Mao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Mao more than expected).

Fields of papers citing papers by M. Mao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. Mao. 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 M. Mao. The network helps show where M. Mao may publish in the future.

Co-authorship network of co-authors of M. Mao

This figure shows the co-authorship network connecting the top 25 collaborators of M. Mao. A scholar is included among the top collaborators of M. Mao 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 M. Mao. M. Mao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Liu, Yingyi, et al.. (2025). Efficient synchronization of high expression and site-specific biotinylation of the PTBP1 RRM3/4 domain. Protein Expression and Purification. 234. 106755–106755.
2.
Mao, M., et al.. (2024). DeepPL: A deep-learning-based tool for the prediction of bacteriophage lifecycle. PLoS Computational Biology. 20(10). e1012525–e1012525. 4 indexed citations
3.
Raciti, David, et al.. (2019). H-Cell Vs Gas Diffusion Electrolyzer for Evaluating Intrinsic Activity of Nanocatalysts for Electrochemical CO2 Reduction. ECS Meeting Abstracts. MA2019-02(22). 1072–1072. 1 indexed citations
4.
Vis, Daniël J., Jeremy Lewin, Rachel G. Liao, et al.. (2017). Towards a global cancer knowledge network: dissecting the current international cancer genomic sequencing landscape. Annals of Oncology. 28(5). 1145–1151. 16 indexed citations
5.
Sak, Haşim, Oriol Vinyals, Georg Heigold, et al.. (2014). Sequence discriminative distributed training of long short-term memory recurrent neural networks. 1209–1213. 96 indexed citations
6.
Zeiler, Matthew D., Rajat Monga, M. Mao, et al.. (2013). On rectified linear units for speech processing. 3517–3521. 315 indexed citations breakdown →
7.
Dean, Jay B., Greg S. Corrado, Rajat Monga, et al.. (2012). Large Scale Distributed Deep Networks. Neural Information Processing Systems. 25. 1223–1231. 1706 indexed citations breakdown →
8.
Mao, M. & Yuanming Pan. (2012). NATURE OF HEAVY METALS IN HEMIMORPHITE: A CATION-EXCHANGE AND SINGLE-CRYSTAL EPR STUDY. The Canadian Mineralogist. 50(1). 31–43. 4 indexed citations
9.
Vanhoucke, Vincent, Andrew Senior, & M. Mao. (2011). Improving the speed of neural networks on CPUs. 384 indexed citations breakdown →
10.
Mao, M., Robert M. Gray, & Tamás Linder. (2011). Rate-Constrained Simulation and Source Coding i.i.d. Sources. IEEE Transactions on Information Theory. 57(7). 4516–4529. 4 indexed citations
11.
Pan, Yuanming, R. I. Mashkovtsev, Dan Huang, M. Mao, & Anton Shatskiy. (2011). Mechanisms of Cr and H incorporation in stishovite determined by single-crystal EPR spectroscopy and DFT calculations. American Mineralogist. 96(8-9). 1331–1342. 6 indexed citations
12.
Mao, M. & Robert M. Gray. (2010). Stationary and Trellis Encoding for IID Sources and Simulation. 3. 3–12.
13.
Pan, Yuanming, M. Mao, & Jinru Lin. (2009). SINGLE-CRYSTAL EPR STUDY OF Fe3+ AND VO2+ IN PREHNITE FROM THE JEFFREY MINE, ASBESTOS, QUEBEC. The Canadian Mineralogist. 47(4). 933–945. 12 indexed citations
14.
Demeter, János, Jin Huang, M. Mao, et al.. (2008). Implementation of GenePattern within the Stanford Microarray Database. Nucleic Acids Research. 37(Database). D898–D901. 88 indexed citations
15.
Mao, M., Vincent Vanhoucke, & Brian Strope. (2006). Automatic Training Set Segmentation for Multi-pass Speech Recognition. 1. 685–688. 2 indexed citations
16.
Oehler, Vivian G., Susan Branford, Era L. Pogosova‐Agadjanyan, et al.. (2005). Gene Expression Signatures Associated with Treatment and Resistance to Imatinib Mesylate in Chronic Myeloid Leukemia Patients.. Blood. 106(11). 433–433. 5 indexed citations
17.
Mao, M. & Vincent Vanhoucke. (2004). Design of compact acoustic models through clustering of tied-covariance Gaussians. 2805–2808. 1 indexed citations
18.

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.

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