Zhaoshi Meng

587 total citations
6 papers, 321 citations indexed

About

Zhaoshi Meng is a scholar working on Artificial Intelligence, Statistics and Probability and Computer Networks and Communications. According to data from OpenAlex, Zhaoshi Meng has authored 6 papers receiving a total of 321 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 3 papers in Statistics and Probability and 2 papers in Computer Networks and Communications. Recurrent topics in Zhaoshi Meng's work include Statistical Methods and Inference (3 papers), Distributed Sensor Networks and Detection Algorithms (2 papers) and Bayesian Modeling and Causal Inference (2 papers). Zhaoshi Meng is often cited by papers focused on Statistical Methods and Inference (3 papers), Distributed Sensor Networks and Detection Algorithms (2 papers) and Bayesian Modeling and Causal Inference (2 papers). Zhaoshi Meng collaborates with scholars based in United States, Israel and China. Zhaoshi Meng's co-authors include Ming Zhang, Qiaozhu Mei, XuanLong Nguyen, Jian Tang, Dileep George, Bhaskara Marthi, Miguel Lázaro-Gredilla, Huayan Wang, Xinghua Lou and Yi Liu and has published in prestigious journals such as Science, IEEE Transactions on Signal Processing and International Conference on Machine Learning.

In The Last Decade

Zhaoshi Meng

6 papers receiving 310 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Zhaoshi Meng United States	5	158	64	55	36	36	6	321
Duncan A. J. Blythe Germany	9	642 4.1×	62 1.0×	86 1.6×	99 2.8×	63 1.8×	14	852
Kevin Robert Canini United States	11	221 1.4×	65 1.0×	118 2.1×	10 0.3×	44 1.2×	16	413
Tejaswini Deoskar United Kingdom	7	579 3.7×	105 1.6×	93 1.7×	17 0.5×	27 0.8×	17	716
Alexander Clark United Kingdom	17	902 5.7×	62 1.0×	57 1.0×	76 2.1×	31 0.9×	66	1.1k
Deokgun Park United States	8	163 1.0×	238 3.7×	52 0.9×	27 0.8×	36 1.0×	10	407
Ian Tenney United States	11	791 5.0×	186 2.9×	102 1.9×	40 1.1×	32 0.9×	13	951
Abdulqader M. Almars Saudi Arabia	13	177 1.1×	95 1.5×	41 0.7×	22 0.6×	25 0.7×	27	375
Cedric De Boom Belgium	7	137 0.9×	38 0.6×	38 0.7×	27 0.8×	25 0.7×	19	227
Eirini Ntoutsi Germany	10	312 2.0×	55 0.9×	74 1.3×	9 0.3×	56 1.6×	52	465

Countries citing papers authored by Zhaoshi Meng

Since Specialization

Citations

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

Fields of papers citing papers by Zhaoshi Meng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhaoshi Meng

This figure shows the co-authorship network connecting the top 25 collaborators of Zhaoshi Meng. A scholar is included among the top collaborators of Zhaoshi Meng 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 Zhaoshi Meng. Zhaoshi Meng 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:

6 of 6 papers shown

1.

George, Dileep, Miguel Lázaro-Gredilla, Bhaskara Marthi, et al.. (2017). A generative vision model that trains with high data efficiency and breaks text-based CAPTCHAs. Science. 358(6368). 151 indexed citations

2.

Tang, Jian, Zhaoshi Meng, XuanLong Nguyen, Qiaozhu Mei, & Ming Zhang. (2014). Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis. International Conference on Machine Learning. 190–198. 128 indexed citations

3.

Meng, Zhaoshi, Dennis Wei, Ami Wiesel, & Alfred O. Hero. (2014). Marginal Likelihoods for Distributed Parameter Estimation of Gaussian Graphical Models. IEEE Transactions on Signal Processing. 62(20). 5425–5438. 10 indexed citations

4.

Meng, Zhaoshi, Dennis Wei, Ami Wiesel, & Alfred O. Hero. (2013). Distributed Learning of Gaussian Graphical Models via Marginal Likelihoods. International Conference on Artificial Intelligence and Statistics. 39–47. 15 indexed citations

5.

Meng, Zhaoshi, Dennis Wei, Alfred O. Hero, & Ami Wiesel. (2013). Marginal likelihoods for distributed estimation of graphical model parameters. 7. 73–76. 2 indexed citations

6.

Meng, Zhaoshi, Ami Wiesel, & Alfred O. Hero. (2012). Distributed principal component analysis on networks via directed graphical models. 17. 2877–2880. 15 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