Mingda Li
Impact in
- Artificial Intelligence top 10%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Graph Neural Networks
- Speech and dialogue systems
Papers in
-
- Topic Modeling 15
- Natural Language Processing Techniques 7
- Advanced Graph Neural Networks 5
- Speech and dialogue systems 4
- Domain Adaptation and Few-Shot Learning 3
-
- Advanced Database Systems and Queries 7
- Co-authors
- Hongzhi Wang (3 shared papers)Jianzhong Li (3 shared papers)Wensheng Zhang (5 shared papers)Zhengya Sun (6 shared papers)Carlo Zaniolo (5 shared papers)Yi Chen (3 shared papers)Jin Wang (5 shared papers)Y. T. Gu (1 shared paper)
- Journals
- Scientific Reports (3 papers)ACM Transactions on Information Systems (2 papers)Neurocomputing (2 papers)Expert Systems with Applications (1 paper)Big Data Mining and Analytics (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Mingda Li
36 papers receiving 230 citations
Peers
Comparison fields: 5 of 57
- Computational Mathematics 3
- Artificial Intelligence 146
- Signal Processing 32
- Management Science and Operations Research 34
- Information Systems 57
Countries citing papers authored by Mingda Li
This map shows the geographic impact of Mingda Li'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 Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingda Li more than expected).
Fields of papers citing papers by Mingda Li
This network shows the impact of papers produced by Mingda Li. 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 Li. The network helps show where Mingda Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Mingda Li, 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 38 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 36 | |
| 2 | 2022 | 26 | |
| 3 | 2021 | 17 | |
| 4 | 2020 | 17 | |
| 5 | 2016 | 16 | |
| 6 | 2020 | 16 | |
| 7 | 2018 | 12 | |
| 8 | 2014 | 8 | |
| 9 | 2025 | 7 | |
| 10 | 2017 | 7 | |
| 11 | 2019 | 6 | |
| 12 | 2021 | 6 | |
| 13 | 2020 | 6 | |
| 14 | 2019 | 6 | |
| 15 | 2023 | 5 | |
| 16 | 2022 | 4 | |
| 17 | 2011 | 4 | |
| 18 | 2022 | 4 | |
| 19 | 2018 | 4 | |
| 20 | 2020 | 4 |
About Mingda Li
Mingda Li is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Signal Processing and Computer Vision and Pattern Recognition, having authored 38 papers that have together received 241 indexed citations. Recurring topics across this work include Topic Modeling (15 papers), Natural Language Processing Techniques (7 papers), Advanced Database Systems and Queries (7 papers), Data Quality and Management (6 papers), Advanced Graph Neural Networks (5 papers), Speech and dialogue systems (4 papers), Data Management and Algorithms (4 papers) and Domain Adaptation and Few-Shot Learning (3 papers). The work is most often cited by research in Computational Mathematics (3 citations), Artificial Intelligence (146 citations), Signal Processing (32 citations), Management Science and Operations Research (34 citations) and Information Systems (57 citations). Mingda Li has collaborated with scholars based in China and United States. Frequent co-authors include Hongzhi Wang, Jianzhong Li, Wensheng Zhang, Zhengya Sun, Carlo Zaniolo, Yi Chen, Jin Wang, Y. T. Gu, Mengxuan Sun and Chunbin Lin. Their work appears in journals such as Scientific Reports, ACM Transactions on Information Systems, Neurocomputing, Expert Systems with Applications and Big Data Mining and Analytics.
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.