Supports integrative research that develops advanced mathematical theories and methods to address complex biological challenges, thereby enhancing our understanding of diverse biological systems and informing public health policy.
Supports integrative research that develops advanced mathematical theories and methods to address complex biological challenges, thereby enhancing our understanding of diverse biological systems and informing public health policy.
Synopsis
The Emerging Mathematics in Biology (eMB) program seeks to stimulate the development of innovative mathematical theories, techniques, and approaches to investigate challenging questions of great interest to biologists and public health policymakers. It supports truly integrative research projects in mathematical biology that address challenging and significant biological questions through novel applications of traditional, but nontrivial, mathematical tools and methods or the development of new mathematical theories particularly from foundational mathematics, including the mathematical foundation of Artificial Intelligence/Deep Learning/Machine Learning (AI/DL/ML) enabling explainable AI or mechanistic insight. The program emphasizes the uses of mathematical methodologies to advance our understanding of complex, dynamic, and heterogenous biological systems at all scales (molecular, cellular, organismal, population, ecosystems, evolutionary, etc.).
Program contacts
| Name | Phone | Organization | |
|---|---|---|---|
|
Zhilan J. Feng Program Director
|
zfeng@nsf.gov | (703) 292-7523 | MPS/DMS |
|
Vu Dinh Program Director
|
vdinh@nsf.gov | (703) 292-4306 | MPS/DMS |