Li Pi
Impact in
- Modeling and Simulation top 10%
- COVID-19 epidemiological studies
- Obstetrics and Gynecology top 10%
- Maternal and Perinatal Health Interventions
Papers in
-
- COVID-19 epidemiological studies 5
-
- SARS-CoV-2 and COVID-19 Research 3
- Co-authors
- Andrea M. Rehman (1 shared paper)Ana Montoya (1 shared paper)Susannah Woodd (1 shared paper)Clara Calvert (1 shared paper)Oona M. R. Campbell (1 shared paper)Doris Chou (1 shared paper)María Barreix (1 shared paper)Yuan Huang (2 shared papers)
- Journals
- Philosophical Transactions of the Royal Society B Biological Sciences (2 papers)Epidemics (1 paper)PLoS Medicine (1 paper)Interface Focus (1 paper)Microbial Cell Factories (1 paper)
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Li Pi
14 papers receiving 260 citations
Peers
Comparison fields: 5 of 87
- Modeling and Simulation 38
- Obstetrics and Gynecology 42
- Pediatrics, Perinatology and Child Health 69
- Health 26
- Infectious Diseases 40
Countries citing papers authored by Li Pi
This map shows the geographic impact of Li Pi'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 Li Pi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Li Pi more than expected).
Fields of papers citing papers by Li Pi
This network shows the impact of papers produced by Li Pi. 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 Li Pi. The network helps show where Li Pi may publish in the future.
Co-authors
The 25 scholars most cited alongside Li Pi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 85 | |
| 2 | 2017 | 49 | |
| 3 | 2021 | 26 | |
| 4 | 2021 | 21 | |
| 5 | 2020 | 21 | |
| 6 | 2020 | 19 | |
| 7 | 2019 | 12 | |
| 8 | 2021 | 9 | |
| 9 | 2017 | 8 | |
| 10 | 2020 | 7 | |
| 11 | 2020 | 4 | |
| 12 | On the use of LFA tests in contact tracing: preliminary findings | 2020 | 4 |
| 13 | 2023 | 3 | |
| 14 | 2014 | 2 |
About Li Pi
Li Pi is a scholar working on Modeling and Simulation, Infectious Diseases, Molecular Biology, Pediatrics, Perinatology and Child Health and Genetics, having authored 14 papers that have together received 270 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (5 papers), Global Maternal and Child Health (3 papers), SARS-CoV-2 and COVID-19 Research (3 papers), Genomics and Chromatin Dynamics (2 papers), COVID-19 Digital Contact Tracing (2 papers), Healthcare Systems and Reforms (2 papers), Genomic variations and chromosomal abnormalities (2 papers) and Oral and gingival health research (1 paper). The work is most often cited by research in Modeling and Simulation (38 citations), Obstetrics and Gynecology (42 citations), Pediatrics, Perinatology and Child Health (69 citations), Health (26 citations) and Infectious Diseases (40 citations). Li Pi has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Andrea M. Rehman, Ana Montoya, Susannah Woodd, Clara Calvert, Oona M. R. Campbell, Doris Chou, María Barreix, Yuan Huang, Jay Pan and Carine Ronsmans. Their work appears in journals such as Philosophical Transactions of the Royal Society B Biological Sciences, Epidemics, PLoS Medicine, Interface Focus and Microbial Cell Factories.
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.