Xiaolu Lu
Impact in
- Infectious Diseases top 10%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- Viral gastroenteritis research and epidemiology
- Animal Science and Zoology top 10%
- Animal Virus Infections Studies
Papers in
-
- Information Retrieval and Search Behavior 11
- Web Data Mining and Analysis 4
-
- Topic Modeling 5
- Co-authors
- Jiali Tao (1 shared paper)Ji‐An Pan (1 shared paper)Deyin Guo (1 shared paper)J. Shane Culpepper (11 shared papers)Alistair Moffat (6 shared papers)Pinghui Feng (2 shared papers)Nick Craswell (2 shared papers)Renjian Xie (1 shared paper)
- Journals
- Information Retrieval (2 papers)Proceedings of the National Academy of Sciences (2 papers)Redox Biology (1 paper)Experimental Cell Research (1 paper)Virus Genes (1 paper)
- Partner nations
- AustraliaChinaUnited States
In The Last Decade
Xiaolu Lu
31 papers receiving 495 citations
Peers
Comparison fields: 5 of 92
- Infectious Diseases 170
- Animal Science and Zoology 53
- Immunology 89
- Information Systems 88
- Agronomy and Crop Science 23
Countries citing papers authored by Xiaolu Lu
This map shows the geographic impact of Xiaolu 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 Xiaolu Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaolu Lu more than expected).
Fields of papers citing papers by Xiaolu Lu
This network shows the impact of papers produced by Xiaolu 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 Xiaolu Lu. The network helps show where Xiaolu Lu may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiaolu 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 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 194 | |
| 2 | 2016 | 44 | |
| 3 | 2023 | 40 | |
| 4 | 2013 | 31 | |
| 5 | 2008 | 25 | |
| 6 | 2021 | 23 | |
| 7 | 2015 | 21 | |
| 8 | 2019 | 20 | |
| 9 | 2024 | 19 | |
| 10 | 2019 | 15 | |
| 11 | 2019 | 12 | |
| 12 | 2015 | 9 | |
| 13 | 2023 | 6 | |
| 14 | 2019 | 6 | |
| 15 | 2017 | 6 | |
| 16 | 2021 | 6 | |
| 17 | 2014 | 4 | |
| 18 | 2016 | 3 | |
| 19 | 2021 | 2 | |
| 20 | 2023 | 2 |
About Xiaolu Lu
Xiaolu Lu is a scholar working on Information Systems, Artificial Intelligence, Computer Vision and Pattern Recognition, Oncology and Signal Processing, having authored 33 papers that have together received 505 indexed citations. Recurring topics across this work include Information Retrieval and Search Behavior (11 papers), Topic Modeling (5 papers), Data Management and Algorithms (4 papers), Web Data Mining and Analysis (4 papers), Advanced Image and Video Retrieval Techniques (4 papers), Image Retrieval and Classification Techniques (3 papers), interferon and immune responses (2 papers) and Data Quality and Management (2 papers). The work is most often cited by research in Infectious Diseases (170 citations), Animal Science and Zoology (53 citations), Immunology (89 citations), Information Systems (88 citations) and Agronomy and Crop Science (23 citations). Xiaolu Lu has collaborated with scholars based in Australia, China and United States. Frequent co-authors include Jiali Tao, Ji‐An Pan, Deyin Guo, J. Shane Culpepper, Alistair Moffat, Pinghui Feng, Nick Craswell, Renjian Xie, İbrahim T. Özbolat and Xiangmin Zhou. Their work appears in journals such as Information Retrieval, Proceedings of the National Academy of Sciences, Redox Biology, Experimental Cell Research and Virus Genes.
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.