Jiarui Lu
Impact in
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- Computational Drug Discovery Methods
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- Machine Learning in Materials Science
- Advanced Nanomaterials in Catalysis
Papers in
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- Greenhouse Technology and Climate Control 7
- Co-authors
- Chaowei Xiao (2 shared papers)Anima Anandkumar (2 shared papers)Jian Tang (2 shared papers)Shengchao Liu (2 shared papers)Weili Nie (2 shared papers)Zhuoran Qiao (1 shared paper)Zhihui Dai (2 shared papers)Min Tao (2 shared papers)
- Journals
- Nature Machine Intelligence (2 papers)Case Studies in Thermal Engineering (2 papers)Applied Thermal Engineering (2 papers)Multiple Sclerosis and Related Disorders (1 paper)ACS Biomaterials Science & Engineering (1 paper)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Jiarui Lu
20 papers receiving 215 citations
Peers
Comparison fields: 5 of 78
- Computational Theory and Mathematics 33
- Materials Chemistry 75
- Business and International Management 3
- Bioengineering 6
- Electrochemistry 6
Countries citing papers authored by Jiarui Lu
This map shows the geographic impact of Jiarui 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 Jiarui Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jiarui Lu more than expected).
Fields of papers citing papers by Jiarui Lu
This network shows the impact of papers produced by Jiarui 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 Jiarui Lu. The network helps show where Jiarui Lu may publish in the future.
Co-authors
The 25 scholars most cited alongside Jiarui 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 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 70 | |
| 2 | 2023 | 30 | |
| 3 | 2022 | 23 | |
| 4 | 2021 | 18 | |
| 5 | 2024 | 12 | |
| 6 | 2023 | 12 | |
| 7 | 2025 | 10 | |
| 8 | 2024 | 8 | |
| 9 | 2023 | 7 | |
| 10 | 2022 | 7 | |
| 11 | 2023 | 6 | |
| 12 | 2024 | 3 | |
| 13 | 2025 | 3 | |
| 14 | 2022 | 3 | |
| 15 | 2023 | 2 | |
| 16 | 2024 | 2 | |
| 17 | 2025 | 1 | |
| 18 | 2025 | 1 | |
| 19 | 2024 | 1 | |
| 20 | 2024 | 1 |
About Jiarui Lu
Jiarui Lu is a scholar working on Plant Science, Molecular Biology, Soil Science, Mechanical Engineering and Materials Chemistry, having authored 23 papers that have together received 220 indexed citations. Recurring topics across this work include Greenhouse Technology and Climate Control (7 papers), Irrigation Practices and Water Management (4 papers), Plant Water Relations and Carbon Dynamics (3 papers), Semantic Web and Ontologies (2 papers), Magnesium Alloys: Properties and Applications (2 papers), Advanced Photocatalysis Techniques (2 papers), Heat Transfer and Optimization (2 papers) and Multiple Sclerosis Research Studies (2 papers). The work is most often cited by research in Computational Theory and Mathematics (33 citations), Materials Chemistry (75 citations), Business and International Management (3 citations), Bioengineering (6 citations) and Electrochemistry (6 citations). Jiarui Lu has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Chaowei Xiao, Anima Anandkumar, Jian Tang, Shengchao Liu, Weili Nie, Zhuoran Qiao, Zhihui Dai, Min Tao, Zhaoyin Wang and Chengpeng Wang. Their work appears in journals such as Nature Machine Intelligence, Case Studies in Thermal Engineering, Applied Thermal Engineering, Multiple Sclerosis and Related Disorders and ACS Biomaterials Science & Engineering.
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.