Ming Dong

418 total citations
18 papers, 268 citations indexed

About

Ming Dong is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Ming Dong has authored 18 papers receiving a total of 268 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 3 papers in Molecular Biology. Recurrent topics in Ming Dong's work include Topic Modeling (6 papers), Misinformation and Its Impacts (3 papers) and Biomedical Text Mining and Ontologies (3 papers). Ming Dong is often cited by papers focused on Topic Modeling (6 papers), Misinformation and Its Impacts (3 papers) and Biomedical Text Mining and Ontologies (3 papers). Ming Dong collaborates with scholars based in China, United States and Australia. Ming Dong's co-authors include Bolong Zheng, Guohui Li, Quoc Viet Hung Nguyen, Alexander Kotov, April Idalski Carcone, Han Su, Farshad Fotouhi, Shiyong Lu, Sylvie Naar‐King and Sylvie Naar and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Image Processing and IEEE Transactions on Neural Networks and Learning Systems.

In The Last Decade

Ming Dong

15 papers receiving 251 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ming Dong China	9	155	74	73	63	33	18	268
Dima Kagan Israel	10	71 0.5×	118 1.6×	72 1.0×	39 0.6×	45 1.4×	16	246
Jiajia Huang China	9	145 0.9×	116 1.6×	42 0.6×	98 1.6×	12 0.4×	16	307
Yanen Li United States	10	148 1.0×	156 2.1×	21 0.3×	16 0.3×	29 0.9×	15	286
Salma Jamoussi Tunisia	11	225 1.5×	61 0.8×	27 0.4×	34 0.5×	14 0.4×	56	330
Akiyo Nadamoto Japan	9	115 0.7×	116 1.6×	78 1.1×	48 0.8×	15 0.5×	64	284
Saurabh Raj Sangwan India	11	230 1.5×	94 1.3×	72 1.0×	26 0.4×	32 1.0×	19	344
Chunyuan Yuan China	7	261 1.7×	147 2.0×	165 2.3×	73 1.2×	31 0.9×	24	376
Aleksandr Farseev Singapore	10	132 0.9×	139 1.9×	50 0.7×	46 0.7×	9 0.3×	21	276
Zhen Lin China	8	89 0.6×	77 1.0×	40 0.5×	139 2.2×	5 0.2×	13	288
Ekaterina Kochmar United Kingdom	9	260 1.7×	68 0.9×	37 0.5×	12 0.2×	23 0.7×	32	331

Countries citing papers authored by Ming Dong

Since Specialization

Citations

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

Fields of papers citing papers by Ming Dong

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming Dong

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

18 of 18 papers shown

Dong, Ming, et al.. (2026). P-CLIP: Progressive Discrepancy Learning for One-Shot Text-to-Image Person Re-Identification. IEEE Transactions on Image Processing. 35. 317–331.

Hu, Po, et al.. (2025). MRBalance: A framework for enhancing event causality identification in multi-agent debates via role assignment. Knowledge-Based Systems. 330. 114470–114470.

Fan, Rui, et al.. (2024). Dual Causes Generation Assisted Model for Multimodal Aspect-Based Sentiment Classification. IEEE Transactions on Neural Networks and Learning Systems. 36(5). 9298–9312. 3 indexed citations

Chen, Wenjing, et al.. (2024). Query-aware multi-scale proposal network for weakly supervised temporal sentence grounding in videos. Knowledge-Based Systems. 304. 112592–112592. 1 indexed citations

Zhao, Wu, et al.. (2024). Spatial Dual Context Learning for Weakly-supervised Group Activity Recognition in Still-images. 1–6. 1 indexed citations

Mao, Qirong, et al.. (2024). Label correlation preserving visual-semantic joint embedding for multi-label zero-shot learning. Multimedia Tools and Applications. 84(20). 22251–22268. 1 indexed citations

Wang, Yufan, et al.. (2023). Incorporating BERT With Probability-Aware Gate for Spoken Language Understanding. IEEE/ACM Transactions on Audio Speech and Language Processing. 31. 826–834. 9 indexed citations

Dong, Ming, Bolong Zheng, Guohui Li, et al.. (2022). Wavefront-Based Multiple Rumor Sources Identification by Multi-Task Learning. IEEE Transactions on Emerging Topics in Computational Intelligence. 6(5). 1068–1078. 13 indexed citations

Li, Guohui, et al.. (2021). Deep reinforcement learning based ensemble model for rumor tracking. Information Systems. 103. 101772–101772. 15 indexed citations

10.

Hu, Qi, et al.. (2020). An Effective Fleet Management Strategy for Collaborative Spatio-Temporal Searching. 651–654. 6 indexed citations

11.

Dong, Ming, Bolong Zheng, Quoc Viet Hung Nguyen, Han Su, & Guohui Li. (2019). Multiple Rumor Source Detection with Graph Convolutional Networks. Griffith Research Online (Griffith University, Queensland, Australia). 569–578. 68 indexed citations

12.

Li, Guohui, Ming Dong, Fuming Yang, et al.. (2019). Misinformation-oriented expert finding in social networks. World Wide Web. 23(2). 693–714. 18 indexed citations

13.

Kotov, Alexander, et al.. (2016). A study of the effectiveness of machine learning methods for classification of clinical interview fragments into a large number of categories. Journal of Biomedical Informatics. 62. 21–31. 43 indexed citations

14.

Dong, Ming, et al.. (2016). Text Classification with Topic-based Word Embedding and Convolutional Neural Networks. 88–97. 37 indexed citations

15.

Kotov, Alexander, et al.. (2015). Interpretable Probabilistic Latent Variable Models for Automatic Annotation of Clinical Text.. PubMed. 2015. 785–94. 9 indexed citations

16.

Dong, Ming, et al.. (2011). Efficiency improvements for a speech recognition coprocessor. 2. 336–339.

17.

Lee, Peng, et al.. (2007). Design of Speech Recognition Co-Processor for the Embedded Implementation. 1. 1163–1166. 7 indexed citations

18.

Lu, Shiyong, Ming Dong, & Farshad Fotouhi. (2002). The Semantic Web: Opportunities and Challenges for Next-Generation Web Applications. SHILAP Revista de lepidopterología. 37 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.

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