Project Grant 2431514

The National Science Foundation (NSF) awarded a $260,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) federal grant program to the University of Texas Rio Grande Valley (UTRGV). The grant, titled "COLLABORATIVE RESEARCH: CISE MSI: RDP: III: TOWARDS ROBUST AND HUMAN-ALIGNED DEEP LEARNING FOR MEDICAL-SENSOR TIME SERIES," aims to develop robust deep learning techniques for analyzing medical sensor time-series data. Specifically, the project seeks to: 1) identify input confounders in time-series data that can lead to spurious correlations, 2) design strategies to mitigate these spurious correlations, and 3) investigate the approach in medical applications such as Parkinson's disease monitoring and fall detection for the elderly. The 3-year project will also support research and educational initiatives to foster broader participation, particularly within the Hispanic community in South Texas. The research outcomes are expected to yield open-source tools that could benefit a wide range of sensor-based medical monitoring and diagnosis tasks.