Fred Lu
Impact in
- Modeling and Simulation top 2%
- COVID-19 epidemiological studies
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
Papers in
-
- Privacy-Preserving Technologies in Data 4
- Stochastic Gradient Optimization Techniques 3
-
- Data-Driven Disease Surveillance 8
- Influenza Virus Research Studies 2
- Co-authors
- Mauricio Santillana (10 shared papers)Leonardo Clemente (5 shared papers)John S. Brownstein (2 shared papers)Mohammad Wasef Hattab (1 shared paper)Matthew Biggerstaff (1 shared paper)André T. Nguyen (3 shared papers)Jessica T. Davis (2 shared papers)Alessandro Vespignani (2 shared papers)
- Journals
- Nature Communications (3 papers)PLoS Computational Biology (3 papers)JMIR Public Health and Surveillance (2 papers)Science Advances (1 paper)PLoS neglected tropical diseases (1 paper)
- Partner nations
- United StatesMexicoAustria
In The Last Decade
Fred Lu
24 papers receiving 655 citations
Peers
Comparison fields: 5 of 80
- Modeling and Simulation 112
- Health Informatics 25
- Epidemiology 254
- Transportation 25
- Public Health, Environmental and Occupational Health 83
Countries citing papers authored by Fred Lu
This map shows the geographic impact of Fred 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 Fred Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fred Lu more than expected).
Fields of papers citing papers by Fred Lu
This network shows the impact of papers produced by Fred 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 Fred Lu. The network helps show where Fred Lu may publish in the future.
Co-authors
The 25 scholars most cited alongside Fred 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 126 | |
| 2 | 2018 | 85 | |
| 3 | 2021 | 84 | |
| 4 | 2019 | 79 | |
| 5 | 2017 | 72 | |
| 6 | 2021 | 52 | |
| 7 | 2024 | 31 | |
| 8 | 2019 | 23 | |
| 9 | 2021 | 23 | |
| 10 | 2022 | 17 | |
| 11 | 2019 | 16 | |
| 12 | 2022 | 13 | |
| 13 | 2022 | 11 | |
| 14 | 2022 | 11 | |
| 15 | 2022 | 5 | |
| 16 | 2023 | 4 | |
| 17 | 2025 | 4 | |
| 18 | 2022 | 2 | |
| 19 | 2023 | 2 | |
| 20 | 2024 | 2 |
About Fred Lu
Fred Lu is a scholar working on Artificial Intelligence, Epidemiology, Modeling and Simulation, Genetics and Public Health, Environmental and Occupational Health, having authored 26 papers that have together received 667 indexed citations. Recurring topics across this work include Data-Driven Disease Surveillance (8 papers), Privacy-Preserving Technologies in Data (4 papers), Genetic Associations and Epidemiology (3 papers), Stochastic Gradient Optimization Techniques (3 papers), COVID-19 epidemiological studies (3 papers), Influenza Virus Research Studies (2 papers), Mosquito-borne diseases and control (2 papers) and Statistical Methods and Inference (1 paper). The work is most often cited by research in Modeling and Simulation (112 citations), Health Informatics (25 citations), Epidemiology (254 citations), Transportation (25 citations) and Public Health, Environmental and Occupational Health (83 citations). Fred Lu has collaborated with scholars based in United States, Mexico and Austria. Frequent co-authors include Mauricio Santillana, Leonardo Clemente, John S. Brownstein, Mohammad Wasef Hattab, Matthew Biggerstaff, André T. Nguyen, Jessica T. Davis, Alessandro Vespignani, Nicholas Link and Matteo Chinazzi. Their work appears in journals such as Nature Communications, PLoS Computational Biology, JMIR Public Health and Surveillance, Science Advances and PLoS neglected tropical diseases.
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.