Ming Yin
- Health Informatics top 0.5%
- Safety Research top 1%
- Ethics and Social Impacts of AI 21
- Experimental Behavioral Economics Studies 6
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- Mobile Crowdsensing and Crowdsourcing 16
- General Decision Sciences top 5%
- Artificial Intelligence top 2%
- Explainable Artificial Intelligence (XAI) 17
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- Aluminum Alloys Composites Properties 7
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- Magnesium Alloys: Properties and Applications 7
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- Human-Automation Interaction and Safety 6
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- Forecasting Techniques and Applications 6
- Co-authors
- Jennifer Wortman VaughanXinru WangHanna WallachZhuoran LuSteven C. BourassaC. ChiangXiao HuYiling Chen
- Journals
- Proceedings of the National Academy of Sciences (1 paper)Nano Letters (1 paper)ACS Nano (1 paper)
- Partner nations
- United StatesChinaSingapore
In The Last Decade
Ming Yin
98 papers receiving 1.9k citations
Hit Papers
Peers
Comparison fields: 5 of 145
- Health Informatics 151
- Safety Research 443
- Computer Science Applications 246
- General Decision Sciences 70
- Artificial Intelligence 733
Countries citing papers authored by Ming Yin
This map shows the geographic impact of Ming Yin'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 Yin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Yin more than expected).
Fields of papers citing papers by Ming Yin
This network shows the impact of papers produced by Ming Yin. 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 Yin. The network helps show where Ming Yin may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ming Yin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 3 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 0 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 24 | |
| 7 | 2024 | 12 | |
| 8 | 2024 | 1 | |
| 9 | 2024 | 3 | |
| 10 | 2024 | 27 | |
| 11 | 2024 | 2 | |
| 12 | 2023 | 37 | |
| 13 | 2023 | 21 | |
| 14 | 2023 | 66 | |
| 15 | 2023 | 10 | |
| 16 | 2023 | 2 | |
| 17 | 2023 | 29 | |
| 18 | 2022 | 18 | |
| 19 | 2020 | 19 | |
| 20 | Bonus or not? learn to reward in crowdsourcing | 2015 | 24 |
About Ming Yin
Ming Yin is a scholar working on Safety Research, Computer Science Applications and Health Informatics, having authored 104 papers that have together received 2.0k indexed citations. Recurring topics across this work include Ethics and Social Impacts of AI (21 papers), Explainable Artificial Intelligence (XAI) (17 papers), Mobile Crowdsensing and Crowdsourcing (16 papers), Aluminum Alloys Composites Properties (7 papers), Magnesium Alloys: Properties and Applications (7 papers), Experimental Behavioral Economics Studies (6 papers), Human-Automation Interaction and Safety (6 papers) and Forecasting Techniques and Applications (6 papers). The work is most often cited by research in Health Informatics (151 citations), Safety Research (443 citations) and Computer Science Applications (246 citations). Ming Yin has collaborated with scholars based in United States, China and Singapore. Frequent co-authors include Jennifer Wortman Vaughan, Xinru Wang, Hanna Wallach, Zhuoran Lu, Steven C. Bourassa, C. Chiang, Xiao Hu, Yiling Chen, Siddharth Suri and Mary L. Gray. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nano Letters and ACS Nano.
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.