Research Grants

Research Grants

R21: Knowledge-informed Deep Learning for Apnea Detection with Limited Annotations

(NIBIB Trailblazer Award for New and Early Stage Investigators)

Funding agency: National Institutes of Health               Role: PI

Period: 09/01/2022-06/30/2025

Co-PIs: Drs. Feng Liu (Stevens Institute of Technology) and Changyue Song

The goal of this research is to create a domain knowledge-informed framework to enable machine learning with limited data availability to generate comprehensive sleep profile learning and monitoring. The technical objective of the proposed study is to construct weakly supervised deep learning models for real-time sleep event detection based on noisy physiological signals with limited annotations.

RAPID: Adaptive Sampling Strategies for COVID-19 Mass Testing

Funding agency: National Science Foundation               Role: PI

Period: 06/01/2020-05/31/2021

Co-PIs: Drs. Jaclyn Hall, Thomas Hladish

Senior Personnel: Dr. Alexander Semenov

The proposal objective is to develop a data-driven strategic framework to optimize COVID-19 mass testing resources and collect community testing data by adaptively sampling within census block groups.

Output: The project generates aggregated COVID-19 datasets about viral and antibody testing in several Florida communities. Detailed descriptions and data can be found at upon request to the PI.

Data Analytics and System Informatics Enhanced Anomaly Detection and Diagnosis for Manufacturing Infrastructure Cybersecurity

Funding Agency: The Florida Center for Cybersecurity             Role: PI

Period: 07/01/2020-06/30/2021

Co-PI: Dr. Devashish Das (University of South Florida)

This project aims to address the interweaved challenges by bridging the knowledge-gaps through to achieve smart cybersecurity-related anomaly detection and fault localization, with a specific focus on applications to manufacturing systems and from the incorporation of data analytics and system-specific domain knowledge.

Safe and Efficient Operations of Autonomous Aircraft for Quick Anomaly Detection

Funding agency: The Florida Space Grant Consortium      Role: PI

Period: 01/01/2022-12/31/2022

In this project, the PI proposes data-driven adaptive strategies to safely and quickly identify abrupt and stochastic abnormalities with autonomous aircraft, integrating concepts of machine learning, uncertainty quantification, statistical process control, mathematical and distributed optimization to dynamically inform online decision making.

Socioeconomic Impacts of COVID-19: A Criminological Perspective

Founding agency: UF Informatics Institute          Role: co-PI

Period: 06/22/2020-12/21/2020

PI: Dr. Yujie Hu

Accountable Artificial Intelligence: Toward Public Interest-Minded News Recommendation Systems

Funding agency: UF Informatics Institute          Role: co-PI

Period: 05/01/2021-04/20/2022

PI: Dr. Jieun Shin

Travel Awards for Research Grant EnhancemenT (TARGET): Factfinding Groundwork for a UF Biofoundry

Funding agency: UF Institute of Food and Agricultural Sciences Dean for Research Office          Role: co-PI

PI: Dr. Andrew Hanson

Thank you for your sponsorship!