Mengyu Xu

Dr. Mengyu Xu is an Associate Professor in the Department of Statistics and Data Science at the University of Central Florida (UCF). She holds a Bachelor's degree from Renmin University of China (2010), and a M.S. and Ph.D. from the University of Chicago (2012 and 2016). Her research focuses on high-dimensional statistical methods, time series analysis, and machine learning applications in diverse fields such as gas turbine performance prediction, terahertz spectroscopy of molecular crystals, and financial market dynamics. She is affiliated with the College of Sciences at UCF and teaches courses in statistics.

Her research interests include covariance matrix estimation, dynamic network recovery from high-dimensional time series, distribution theory of quadratic forms, and hypothesis testing. Notably, she has contributed to advancements in fentanyl detection via terahertz spectroscopy and anomaly detection in industrial systems. Her work bridges statistical theory with practical applications in engineering, finance, and chemistry.

Publications highlight her expertise in high-dimensional data analysis, machine learning integration with traditional statistical methods, and the development of novel methodologies for real-world challenges such as drug identification and predictive maintenance in gas turbines. She has explored asymmetric self-exciting processes in Bitcoin returns and contextual factors influencing student performance in online education environments.

Labs/Teams: While no specific lab or team names are listed, her work suggests collaboration with interdisciplinary groups in data science, engineering, and computational chemistry at UCF.