Mingda Zhang

50 total papers · 510 total citations
22 papers, 332 citations indexed

About

Mingda Zhang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Mingda Zhang has authored 22 papers receiving a total of 332 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 8 papers in Computer Vision and Pattern Recognition and 6 papers in Signal Processing. Recurrent topics in Mingda Zhang's work include Multimodal Machine Learning Applications (6 papers), Data Management and Algorithms (5 papers) and Geographic Information Systems Studies (4 papers). Mingda Zhang is often cited by papers focused on Multimodal Machine Learning Applications (6 papers), Data Management and Algorithms (5 papers) and Geographic Information Systems Studies (4 papers). Mingda Zhang collaborates with scholars based in China, United States and Switzerland. Mingda Zhang's co-authors include Zhenyu Tan, Peng Yue, Liying Guo, Meiling Gao, Liping Di, Adriana Kovashka, Liangcun Jiang, Chenxiao Zhang, Jesse Berent and Danfeng Qin and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Remote Sensing and Environmental Modelling & Software.

In The Last Decade

Mingda Zhang

19 papers receiving 321 citations

Author Peers

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

Author						Papers	Cites
Mingda Zhang	123	97	89	57	48	22	332
Hannah Augustin	29 0.2×	65 0.7×	90 1.0×	25 0.4×	50 1.0×	18	353
Minseo Kang	45 0.4×	25 0.3×	75 0.8×	32 0.6×	67 1.4×	10	351
Baoxuan Jin	31 0.3×	34 0.4×	40 0.4×	33 0.6×	27 0.6×	27	350
Allae Erraissi	27 0.2×	49 0.5×	55 0.6×	58 1.0×	8 0.2×	38	301
Daniel Nüst	36 0.3×	12 0.1×	74 0.8×	121 2.1×	39 0.8×	29	304
Dongying Zhang	26 0.2×	42 0.4×	59 0.7×	16 0.3×	6 0.1×	31	330
Norbert Widmann	44 0.4×	13 0.1×	78 0.9×	70 1.2×	46 1.0×	10	319
Yan Xu	29 0.2×	15 0.2×	47 0.5×	61 1.1×	111 2.3×	12	389
Robert Jeansoulin	24 0.2×	16 0.2×	93 1.0×	15 0.3×	139 2.9×	25	308
Jie Yu	230 1.9×	20 0.2×	79 0.9×	4 0.1×	44 0.9×	26	400

Countries citing papers authored by Mingda Zhang

Since Specialization

Citations

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

Fields of papers citing papers by Mingda Zhang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mingda Zhang

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