Dr. Xuyu Wang is PI of a new National Science Foundation Award
Dr. Xuyu Wang, Assistant Professor in the Knight Foundation School of Computing and Information Sciences (KFSCIS) is the PI of a new National Science Foundation (NSF) award, entitled “Collaborative Research: IMR: MM-1A: Functional Data Analysis-aided Learning Methods for Robust Wireless Measurements.” The award totals $200,000 over three years. The collaborative partner, Auburn University, will receive approximately $400,000, making this project total $600,000.
To quote from the abstract of the new project:
“With the growth of large-scale, heterogeneous, dynamic, and complex wireless networks, how to achieve accurate and robust measurements in 5G networks and beyond becomes a challenging and important problem.” … “The proposed research falls into the following four interwoven thrusts. (i) Functional Data Regression for Sparse Wireless Measurements: to develop a deep learning-based approach to address fundamental regression problems of functional data. (ii) FDA-based Transfer Learning for Dynamic Wireless Measurements: to study transfer learning for functional data regression and classification under the distribution shift between test data and training data for effective wireless measurements in dynamic environments. (iii) Quantile FDA-based Learning for Robust Wireless Measurements and Control: to develop a deep learning-based approach to address the fundamental bottleneck of quantile regression-based methods. (iv) Wireless Measurement Applications for Integration and Validation.”
The full abstract can be found at https://www.nsf.gov/awardsearch/showAward?AWD_ID=2319343
This is the second NSF award received this month by Dr. Wang. The other award was for “AI-driven RFID Sensing for Smart Health Applications,” which totals an additional $300,000 over four years to FIU.