Joan Lu
Impact in
- Signal Processing top 5%
- Data Management and Algorithms
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- Energy Efficient Wireless Sensor Networks
- IoT and Edge/Fog Computing
Papers in
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- Data Mining Algorithms and Applications 11
- Cloud Computing and Resource Management 9
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- Semantic Web and Ontologies 16
- Co-authors
- Qiang Xu (49 shared papers)Kamin Whitehouse (1 shared paper)Hui Li (2 shared papers)Guijun Xian (2 shared papers)Fadi Thabtah (11 shared papers)Lizhen Wang (2 shared papers)Marianne Cherrington (9 shared papers)Gang Zhou (1 shared paper)
- Journals
- Materials at High Temperatures (6 papers)PLoS ONE (3 papers)Sensors (2 papers)Information Sciences (1 paper)Scientific Reports (1 paper)
- Partner nations
- United KingdomChinaNew Zealand
In The Last Decade
Joan Lu
174 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 146
- Signal Processing 209
- Computer Networks and Communications 422
- Information Systems 413
- Artificial Intelligence 333
- Health Informatics 12
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 185 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 120 | |
| 2 | 2015 | 98 | |
| 3 | 2009 | 97 | |
| 4 | 2019 | 73 | |
| 5 | 2009 | 69 | |
| 6 | 2018 | 64 | |
| 7 | 2008 | 47 | |
| 8 | 2021 | 43 | |
| 9 | 2022 | 40 | |
| 10 | 2014 | 38 | |
| 11 | 2009 | 34 | |
| 12 | 2017 | 30 | |
| 13 | 2015 | 30 | |
| 14 | 2020 | 26 | |
| 15 | 2021 | 25 | |
| 16 | 2001 | 25 | |
| 17 | 2016 | 25 | |
| 18 | Proceedings of The 2005 International Conference on Internet Computing, ICOMP 2005 | 2007 | 24 |
| 19 | 2017 | 22 | |
| 20 | 2013 | 19 |
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 185 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced Database Systems and Queries (17 papers), High Temperature Alloys and Creep (17 papers), Semantic Web and Ontologies (16 papers), Fatigue and fracture mechanics (16 papers), Data Management and Algorithms (15 papers), Metallurgy and Material Forming (13 papers), Data Mining Algorithms and Applications (11 papers) and Cloud Computing and Resource Management (9 papers). The work is most often cited by research in Signal Processing (209 citations), Computer Networks and Communications (422 citations), Information Systems (413 citations), Artificial Intelligence (333 citations) and Health Informatics (12 citations). Joan Lu has collaborated with scholars based in United Kingdom, China and New Zealand. Frequent co-authors include Qiang Xu, Kamin Whitehouse, Hui Li, Guijun Xian, Fadi Thabtah, Lizhen Wang, Marianne Cherrington, Gang Zhou, Chieh‐Yih Wan and Mark Yarvis. Their work appears in journals such as Materials at High Temperatures, PLoS ONE, Sensors, Information Sciences and Scientific Reports.
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.