Ming Gong

112 total papers · 5.8k total citations
52 papers, 2.6k citations indexed

About

Ming Gong is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Ming Gong has authored 52 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Artificial Intelligence, 19 papers in Computer Vision and Pattern Recognition and 7 papers in Information Systems. Recurrent topics in Ming Gong's work include Topic Modeling (29 papers), Natural Language Processing Techniques (27 papers) and Multimodal Machine Learning Applications (14 papers). Ming Gong is often cited by papers focused on Topic Modeling (29 papers), Natural Language Processing Techniques (27 papers) and Multimodal Machine Learning Applications (14 papers). Ming Gong collaborates with scholars based in China, United States and Canada. Ming Gong's co-authors include Daxin Jiang, Nan Duan, Linjun Shou, Ming Zhou, Duyu Tang, Daya Guo, Zhangyin Feng, Xiaocheng Feng, Ting Liu and Bing Qin and has published in prestigious journals such as SHILAP Revista de lepidopterología, Medicine and Remote Sensing.

In The Last Decade

Ming Gong

50 papers receiving 2.6k citations

Hit Papers

CodeBERT: A Pre-Trained M... 2020 2026 2022 2024 2020 2020 400 800 1.2k

Author Peers

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

Author Last Decade Papers Cites
Ming Gong 1.6k 1.1k 680 511 364 52 2.6k
Xiaocheng Feng 1.8k 1.1× 1.2k 1.1× 222 0.3× 508 1.0× 356 1.0× 64 2.8k
Linjun Shou 1.2k 0.7× 1.1k 1.0× 239 0.4× 511 1.0× 347 1.0× 39 2.0k
Lei Ma 2.2k 1.3× 1.0k 0.9× 755 1.1× 1.2k 2.3× 620 1.7× 148 3.6k
Shiqing Ma 1.6k 1.0× 540 0.5× 374 0.6× 311 0.6× 859 2.4× 60 2.5k
T.L. McCluskey 1.4k 0.9× 774 0.7× 336 0.5× 164 0.3× 359 1.0× 103 2.2k
Daya Guo 1.3k 0.8× 1.5k 1.4× 183 0.3× 752 1.5× 475 1.3× 21 2.3k
Ming Li 610 0.4× 825 0.8× 259 0.4× 550 1.1× 265 0.7× 56 1.9k
Lili Mou 1.7k 1.1× 608 0.6× 353 0.5× 265 0.5× 222 0.6× 59 2.2k
Baishakhi Ray 1.4k 0.9× 1.9k 1.8× 301 0.4× 1.4k 2.7× 735 2.0× 80 3.5k
Suman Jana 2.1k 1.3× 1.1k 1.0× 963 1.4× 831 1.6× 1.2k 3.3× 65 3.9k

Countries citing papers authored by Ming Gong

Since Specialization
Citations

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

Fields of papers citing papers by Ming Gong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming Gong

This figure shows the co-authorship network connecting the top 25 collaborators of Ming Gong. A scholar is included among the top collaborators of Ming Gong 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 Gong. Ming Gong 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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