Selin Aviyente, Professor of Electrical and Computer Engineering, is part of the team led by Tapabrata Maiti, Professor of Department of Statistics & Probability, that received a new NSF award to develop next-generation statistical theory and methods of machine learning for new age spatio-temporal data.
This project aims to provide a broader and nonstandard framework for handling massive spatio-temporal data that are arising in technology-based modern world contexts such as computer vision, self-driving cars, and imaging. The techniques are well established in applied machine learning literature but distinguish themselves from the traditional spatio-temporal analysis in statistics. The project will advance research in high dimensional machine learning theory and methods, and will provide training opportunities for undergraduate and graduate students studying statistics, machine learning, and data science. More details about the project could be found in: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1924724&HistoricalAwards=false.