Division of Electrical, Communications and Cyber Systems
Multimodal Sensor Systems for Precision Health Enabled by Data Harnessing, Artificial Intelligence, and Learning (SenSE)
|Radhakisan S. Bahetifirstname.lastname@example.org||(703) 292-8339|
|Shubhra Gangopadhyayemail@example.com||(703) 292-2485|
|Laurel C. Kuxhausfirstname.lastname@example.org||(703) 292-4465|
|Wendy Nilsenemail@example.com||(703) 292-2568|
|Robert A. Scheidtfirstname.lastname@example.org||703-292-2477|
|Aleksandr L. Simonianemail@example.com||(703) 292-2191|
|Usha Varshneyfirstname.lastname@example.org||(703) 292-8339|
|Albert Z. Wangemail@example.com||(703) 292-7230|
|Huixia Wangfirstname.lastname@example.org||(703) 292-2279|
Important Information for Proposers
A revised version of the NSF Proposal & Award Policies & Procedures Guide (PAPPG) (NSF 20-1), is effective for proposals submitted, or due, on or after June 1, 2020. Please be advised that, depending on the specified due date, the guidelines contained in NSF 20-1 may apply to proposals submitted in response to this funding opportunity.
Full Proposal Deadline Date
June 8, 2020
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.