Yeye He
Impact in
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- Data Quality and Management
- Artificial Intelligence top 2%
- Privacy-Preserving Technologies in Data
- Topic Modeling
- Cryptography and Data Security
- Semantic Web and Ontologies
Papers in
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- Data Quality and Management 30
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- Data Management and Algorithms 15
- Co-authors
- Jeffrey F. Naughton (4 shared papers)Surajit Chaudhuri (17 shared papers)Chen Zhao (1 shared paper)Xin Luna Dong (2 shared papers)Kris Ganjam (8 shared papers)Cong Yan (1 shared paper)Kaushik Chakrabarti (6 shared papers)A.D.N. Sarma (1 shared paper)
- Journals
- Proceedings of the VLDB Endowment (12 papers)ACM SIGMOD Record (1 paper)International Conference on Management of Data (1 paper)IEEE Data(base) Engineering Bulletin (1 paper)Max Planck Digital Library (2 papers)
- Partner nations
- United StatesUnited KingdomChina
In The Last Decade
Yeye He
45 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 46
- Management Science and Operations Research 499
- Artificial Intelligence 691
- Signal Processing 191
- Information Systems 365
- Information Systems and Management 82
Countries citing papers authored by Yeye He
This map shows the geographic impact of Yeye He'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 Yeye He with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yeye He more than expected).
Fields of papers citing papers by Yeye He
This network shows the impact of papers produced by Yeye He. 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 Yeye He. The network helps show where Yeye He may publish in the future.
Co-authors
The 25 scholars most cited alongside Yeye He, 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 47 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 163 | |
| 2 | 2019 | 88 | |
| 3 | 2014 | 65 | |
| 4 | 2011 | 63 | |
| 5 | 2017 | 49 | |
| 6 | 2020 | 49 | |
| 7 | 2018 | 41 | |
| 8 | 2013 | 40 | |
| 9 | 2024 | 36 | |
| 10 | 2011 | 33 | |
| 11 | 2015 | 33 | |
| 12 | 2018 | 32 | |
| 13 | 2010 | 31 | |
| 14 | 2019 | 30 | |
| 15 | 2015 | 25 | |
| 16 | 2015 | 24 | |
| 17 | 2016 | 21 | |
| 18 | 2013 | 20 | |
| 19 | 2021 | 19 | |
| 20 | 2017 | 19 |
About Yeye He
Yeye He is a scholar working on Management Science and Operations Research, Signal Processing, Computer Networks and Communications, Information Systems and Artificial Intelligence, having authored 47 papers that have together received 1.1k indexed citations. Recurring topics across this work include Data Quality and Management (30 papers), Advanced Database Systems and Queries (18 papers), Data Management and Algorithms (15 papers), Web Data Mining and Analysis (14 papers), Semantic Web and Ontologies (6 papers), Topic Modeling (6 papers), Privacy-Preserving Technologies in Data (4 papers) and Software Engineering Research (3 papers). The work is most often cited by research in Management Science and Operations Research (499 citations), Artificial Intelligence (691 citations), Signal Processing (191 citations), Information Systems (365 citations) and Information Systems and Management (82 citations). Yeye He has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Jeffrey F. Naughton, Surajit Chaudhuri, Chen Zhao, Xin Luna Dong, Kris Ganjam, Cong Yan, Kaushik Chakrabarti, A.D.N. Sarma, Zhipeng Huang and Erkang Zhu. Their work appears in journals such as Proceedings of the VLDB Endowment, ACM SIGMOD Record, International Conference on Management of Data, IEEE Data(base) Engineering Bulletin and Max Planck Digital Library.
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.