Mingxin Gan
Impact in
- Information Systems top 2%
- Recommender Systems and Techniques
- Transportation top 5%
- Human Mobility and Location-Based Analysis
Papers in
-
- Recommender Systems and Techniques 44
-
- Advanced Graph Neural Networks 20
- Topic Modeling 8
- Co-authors
- Rui Jiang (19 shared papers)Peng He (1 shared paper)Ling Gao (2 shared papers)H. Y. Zhang (5 shared papers)Shengquan Chen (1 shared paper)Hairong Lv (1 shared paper)Xiongtao Zhang (5 shared papers)Jiaxin Wu (4 shared papers)
- Journals
- Expert Systems with Applications (6 papers)World Wide Web (5 papers)Information Processing & Management (3 papers)BMC Systems Biology (3 papers)Knowledge-Based Systems (2 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Mingxin Gan
61 papers receiving 652 citations
Peers
Comparison fields: 5 of 94
- Information Systems 375
- Transportation 69
- Artificial Intelligence 248
- Statistical and Nonlinear Physics 59
- Management Science and Operations Research 55
Countries citing papers authored by Mingxin Gan
This map shows the geographic impact of Mingxin Gan'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 Mingxin Gan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingxin Gan more than expected).
Fields of papers citing papers by Mingxin Gan
This network shows the impact of papers produced by Mingxin Gan. 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 Mingxin Gan. The network helps show where Mingxin Gan may publish in the future.
Co-authors
The 25 scholars most cited alongside Mingxin Gan, 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 68 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 71 | |
| 2 | 2011 | 68 | |
| 3 | 2013 | 45 | |
| 4 | 2013 | 32 | |
| 5 | 2022 | 26 | |
| 6 | 2014 | 25 | |
| 7 | 2021 | 25 | |
| 8 | 2019 | 22 | |
| 9 | 2021 | 21 | |
| 10 | 2019 | 20 | |
| 11 | 2015 | 20 | |
| 12 | 2022 | 20 | |
| 13 | 2021 | 19 | |
| 14 | 2022 | 18 | |
| 15 | 2023 | 16 | |
| 16 | 2020 | 15 | |
| 17 | 2022 | 15 | |
| 18 | 2015 | 14 | |
| 19 | 2023 | 12 | |
| 20 | 2021 | 11 |
About Mingxin Gan
Mingxin Gan is a scholar working on Information Systems, Artificial Intelligence, Molecular Biology, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics, having authored 68 papers that have together received 672 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (44 papers), Advanced Graph Neural Networks (20 papers), Machine Learning in Bioinformatics (12 papers), Complex Network Analysis Techniques (11 papers), Bioinformatics and Genomic Networks (10 papers), Human Mobility and Location-Based Analysis (8 papers), Topic Modeling (8 papers) and Advanced Bandit Algorithms Research (6 papers). The work is most often cited by research in Information Systems (375 citations), Transportation (69 citations), Artificial Intelligence (248 citations), Statistical and Nonlinear Physics (59 citations) and Management Science and Operations Research (55 citations). Mingxin Gan has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Rui Jiang, Peng He, Ling Gao, H. Y. Zhang, Shengquan Chen, Hairong Lv, Xiongtao Zhang, Jiaxin Wu, Qiao Liu and Lingling Yi. Their work appears in journals such as Expert Systems with Applications, World Wide Web, Information Processing & Management, BMC Systems Biology and Knowledge-Based Systems.
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.