Ming Tan
Impact in
- Software top 2%
- Software Reliability and Analysis Research
- Software Testing and Debugging Techniques
- Information Systems top 2%
- Software Engineering Research
Papers in
-
- Topic Modeling 10
- Natural Language Processing Techniques 8
- Domain Adaptation and Few-Shot Learning 3
- Speech and dialogue systems 3
-
- Advanced Neural Network Applications 3
- Co-authors
- Lin Tan (2 shared papers)Sashank Dara (2 shared papers)Bing Xiang (2 shared papers)Bowen Zhou (2 shared papers)Cícero dos Santos (1 shared paper)Larry J. Eshelman (1 shared paper)John McDermott (1 shared paper)Shaojun Wang (5 shared papers)
- Journals
- Proceedings of the ACM on Human-Computer Interaction (2 papers)Industrial Crops and Products (2 papers)Remote Sensing (2 papers)Computational Linguistics (1 paper)Journal of Food Composition and Analysis (1 paper)
- Partner nations
- ChinaUnited StatesIndia
In The Last Decade
Ming Tan
39 papers receiving 853 citations
Peers
Comparison fields: 5 of 99
- Software 249
- Information Systems 408
- Artificial Intelligence 442
- Computer Networks and Communications 143
- Computer Science Applications 28
Countries citing papers authored by Ming Tan
This map shows the geographic impact of Ming Tan'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 Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Tan more than expected).
Fields of papers citing papers by Ming Tan
This network shows the impact of papers produced by Ming Tan. 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 Tan. The network helps show where Ming Tan may publish in the future.
Co-authors
The 25 scholars most cited alongside Ming Tan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 187 | |
| 2 | 2016 | 160 | |
| 3 | 2015 | 118 | |
| 4 | 1987 | 102 | |
| 5 | 1997 | 36 | |
| 6 | 2022 | 27 | |
| 7 | 2019 | 26 | |
| 8 | 2020 | 25 | |
| 9 | 2022 | 20 | |
| 10 | 2024 | 17 | |
| 11 | 2012 | 16 | |
| 12 | 2019 | 15 | |
| 13 | 2022 | 15 | |
| 14 | 2023 | 12 | |
| 15 | 2013 | 12 | |
| 16 | 2012 | 11 | |
| 17 | Direct 0-1 Loss Minimization and Margin Maximization with Boosting | 2013 | 10 |
| 18 | 2023 | 10 | |
| 19 | 2022 | 10 | |
| 20 | 2023 | 7 |
About Ming Tan
Ming Tan is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Information Systems and Marketing, having authored 43 papers that have together received 892 indexed citations. Recurring topics across this work include Topic Modeling (10 papers), Natural Language Processing Techniques (8 papers), Customer churn and segmentation (4 papers), Data Management and Algorithms (3 papers), Biochemical Analysis and Sensing Techniques (3 papers), Advanced Neural Network Applications (3 papers), Domain Adaptation and Few-Shot Learning (3 papers) and Speech and dialogue systems (3 papers). The work is most often cited by research in Software (249 citations), Information Systems (408 citations), Artificial Intelligence (442 citations), Computer Networks and Communications (143 citations) and Computer Science Applications (28 citations). Ming Tan has collaborated with scholars based in China, United States and India. Frequent co-authors include Lin Tan, Sashank Dara, Bing Xiang, Bowen Zhou, Cícero dos Santos, Larry J. Eshelman, John McDermott, Shaojun Wang, Lixiang Xu and Dakuo Wang. Their work appears in journals such as Proceedings of the ACM on Human-Computer Interaction, Industrial Crops and Products, Remote Sensing, Computational Linguistics and Journal of Food Composition and Analysis.
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.