Mingcong Song

25 total papers · 651 total citations
22 papers, 475 citations indexed

About

Mingcong Song is a scholar working on Information Systems, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Mingcong Song has authored 22 papers receiving a total of 475 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Information Systems, 9 papers in Computer Vision and Pattern Recognition and 8 papers in Computer Networks and Communications. Recurrent topics in Mingcong Song's work include Advanced Neural Network Applications (9 papers), Cloud Computing and Resource Management (8 papers) and Parallel Computing and Optimization Techniques (5 papers). Mingcong Song is often cited by papers focused on Advanced Neural Network Applications (9 papers), Cloud Computing and Resource Management (8 papers) and Parallel Computing and Optimization Techniques (5 papers). Mingcong Song collaborates with scholars based in United States and China. Mingcong Song's co-authors include Tao Li, Yang Hu, Jiaqi Zhang, Huixiang Chen, Tao Li, Jingling Yuan, Yuting Dai, Xiaoyao Liang, Chao Li and Jing Wang and has published in prestigious journals such as IEEE Transactions on Computers, IEEE Geoscience and Remote Sensing Letters and ACM SIGPLAN Notices.

In The Last Decade

Mingcong Song

21 papers receiving 466 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Mingcong Song	233	188	156	146	85	22	475
Tianwei Xing	253 1.1×	192 1.0×	229 1.5×	63 0.4×	55 0.6×	15	502
Alessandro Capotondi	140 0.6×	173 0.9×	118 0.8×	149 1.0×	29 0.3×	32	458
Zhuoran Zhao	181 0.8×	159 0.8×	116 0.7×	254 1.7×	35 0.4×	17	456
Hanqing Zeng	224 1.0×	264 1.4×	222 1.4×	106 0.7×	19 0.2×	22	538
Xiang Wang	176 0.8×	136 0.7×	81 0.5×	211 1.4×	20 0.2×	26	520
Duncan J. M. Moss	214 0.9×	268 1.4×	162 1.0×	100 0.7×	22 0.3×	13	513
Yaman Umuroglu	264 1.1×	228 1.2×	160 1.0×	75 0.5×	15 0.2×	12	454
Qiang Yin	220 0.9×	39 0.2×	218 1.4×	99 0.7×	76 0.9×	33	508
Vaishnav Srinivas	111 0.5×	316 1.7×	129 0.8×	182 1.2×	38 0.4×	22	510
José-María Arnau	169 0.7×	128 0.7×	125 0.8×	176 1.2×	42 0.5×	37	458

Countries citing papers authored by Mingcong Song

Since Specialization

Citations

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

Fields of papers citing papers by Mingcong Song

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mingcong Song

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

All Works

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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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