Multimodal Sensor Systems for Precision Health Enabled by Data Harnessing, Artificial Intelligence, and Learning (SenSE)

The National Science Foundation (NSF) through its Divisions of Electrical, Communications and Cyber Systems (ECCS); Chemical, Bioengineering, Environmental and Transport Systems (CBET); Civil, Mechanical and Manufacturing Innovation (CMMI); Information and Intelligent Systems (IIS); and Mathematical Sciences (DMS) announces a solicitation on Multimodal Sensor Systems for Precision Health enabled by Data Harnessing, Artificial Intelligence (AI), and Learning. Next-generation multimodal sensor systems for precision health integrated with AI, machine learning (ML), and mathematical and statistical (MS) methods for learning can be envisioned for harnessing a large volume of diverse data in real time with high accuracy, sensitivity and selectivity, and for building predictive models to enable more precise diagnosis and individualized treatments. It is expected that these multimodal sensor systems will have the potential to identify with high confidence combinations of biomarkers, including kinematic and kinetic indicators associated with specific disease and disability. This focused solicitation seeks high-risk/high-return interdisciplinary research on novel concepts, innovative methodologies, theory, algorithms, and enabling technologies that will address the fundamental scientific issues and technological challenges associated with precision health.