Cited Research (published between 4/2020 and 2/2024; all PDFs available here)
- Han BA, O’Regan SM, Paul Schmidt J, Drake JM. Integrating data mining and transmission theory in the ecology of infectious diseases. Ecol Lett. 2020;23: 1178–1188. doi:10.1111/ele.13520
- Fischhoff IR, Castellanos AA, Rodrigues JPGL, Varsani A, Han BA. Predicting the zoonotic capacity of mammal species for SARS-CoV-2. Proceedings of the Royal Society B. 2021;288: 2021.02.18.431844. doi:10.1098/rspb.2021.1651
- Wadhawan K, Das P, Han BA, Fischhoff IR, Castellanos AC, Varsani A, Varshney K. Towards Interpreting Zoonotic Potential of Betacoronavirus Sequences With Attention. ICLR 2021 Workshop: Machine learning for preventing and combating pandemics. 2021. Available: http://arxiv.org/abs/2108.08077
*ICLR is the International Conference of Learning Representations, a machine learning / AI conference where research papers are peer-reviewed and, if accepted, they are presented and published as conference proceedings. This is the standard process in AI research, and ICLR is one of the premier conferences in the field. - Ecke F, Han BA, Hörnfeldt B, Khalil H, Magnusson M, Singh NJ, et al. Population fluctuations and synanthropy explain transmission risk in rodent-borne zoonoses. Nat Commun. 2022;13: 1–10. doi:10.1038/s41467-022-35273-7
- Rosi EJ, Fick JB, Han BA. Are Animal Disease Reservoirs at Risk of Human Antiviral Exposure? Environ Sci Technol Lett. 2023. doi:10.1021/acs.estlett.3c00201
- Han BA, Varshney KR, LaDeau S, Subramaniam A, Weathers KC, Zwart J. A synergistic future for AI and ecology. Proc Natl Acad Sci U S A. 2023;120: e2220283120. doi:10.1073/pnas.2220283120