Joan Lu
Impact in
- Signal Processing top 2%
- Data Management and Algorithms
- Information Systems top 2%
- Data Mining Algorithms and Applications
Papers in
-
- Mobile Learning in Education 13
- Data Mining Algorithms and Applications 12
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- Semantic Web and Ontologies 20
- Co-authors
- Qiang Xu (61 shared papers)Fadi Thabtah (13 shared papers)Kamin Whitehouse (1 shared paper)Hui Li (2 shared papers)Guijun Xian (2 shared papers)Lizhen Wang (3 shared papers)Marianne Cherrington (11 shared papers)Gang Zhou (1 shared paper)
- Journals
- Materials at High Temperatures (7 papers)PLoS ONE (5 papers)Sensors (2 papers)Energy Geoscience (1 paper)Mobile Networks and Applications (1 paper)
- Partner nations
- United KingdomChinaNew Zealand
In The Last Decade
Joan Lu
221 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 151
- Signal Processing 288
- Information Systems 542
- Computer Networks and Communications 497
- Artificial Intelligence 400
- Health Informatics 13
Countries citing papers authored by Joan Lu
This map shows the geographic impact of Joan Lu'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 Joan Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joan Lu more than expected).
Fields of papers citing papers by Joan Lu
This network shows the impact of papers produced by Joan Lu. 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 Joan Lu. The network helps show where Joan Lu may publish in the future.
Co-authors
The 25 scholars most cited alongside Joan Lu, 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 243 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 128 | |
| 2 | 2015 | 105 | |
| 3 | 2009 | 103 | |
| 4 | 2009 | 99 | |
| 5 | 2019 | 82 | |
| 6 | 2018 | 77 | |
| 7 | 2008 | 58 | |
| 8 | 2022 | 48 | |
| 9 | 2009 | 48 | |
| 10 | 2021 | 45 | |
| 11 | 2014 | 40 | |
| 12 | 2017 | 38 | |
| 13 | 2015 | 31 | |
| 14 | Proceedings of The 2005 International Conference on Internet Computing, ICOMP 2005 | 2007 | 29 |
| 15 | 2020 | 28 | |
| 16 | 2021 | 27 | |
| 17 | 2017 | 27 | |
| 18 | 2001 | 27 | |
| 19 | 2016 | 26 | |
| 20 | 2020 | 23 |
About Joan Lu
Joan Lu is a scholar working on Information Systems, Artificial Intelligence, Computer Networks and Communications, Mechanical Engineering and Mechanics of Materials, having authored 243 papers that have together received 2.0k indexed citations. Recurring topics across this work include High Temperature Alloys and Creep (25 papers), Advanced Database Systems and Queries (23 papers), Data Management and Algorithms (21 papers), Fatigue and fracture mechanics (20 papers), Semantic Web and Ontologies (20 papers), Metallurgy and Material Forming (19 papers), Mobile Learning in Education (13 papers) and Data Mining Algorithms and Applications (12 papers). The work is most often cited by research in Signal Processing (288 citations), Information Systems (542 citations), Computer Networks and Communications (497 citations), Artificial Intelligence (400 citations) and Health Informatics (13 citations). Joan Lu has collaborated with scholars based in United Kingdom, China and New Zealand. Frequent co-authors include Qiang Xu, Fadi Thabtah, Kamin Whitehouse, Hui Li, Guijun Xian, Lizhen Wang, Marianne Cherrington, Gang Zhou, John A. Stankovic and Lihua Zhou. Their work appears in journals such as Materials at High Temperatures, PLoS ONE, Sensors, Energy Geoscience and Mobile Networks and Applications.
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.