معرفی
David Hitchcock is a Professor of Statistics at the University of South Carolina, serving as Director of the Graduate Program in the Department of Statistics within the McCausland College of Arts and Sciences. He earned his B.S. from the University of Georgia, M.S. from Clemson University, and Ph.D. from the University of Florida. His research focuses on functional data analysis, cluster analysis, and environmental applications, including spatio-temporal modeling of precipitation, medical skill assessment, and wildfire data analysis.
Education:
- Bachelor’s Degree: University of Georgia
- Master’s Degree: Clemson University (Mathematical Sciences)
- Ph.D.: University of Florida (Statistics)
Research Interests:
Hitchcock’s work spans functional data analysis, cluster analysis, and environmental statistics. Recent projects include:
- Simultaneous registration and clustering of functional data in medical skill evaluation.
- Spatio-temporal models for flood dynamics and precipitation patterns.
- Applications in loggerhead turtle population estimation and mass spectrometry.
Collaborations:
He collaborates with researchers like John Grego (flooding data), Ian Dryden (proteomics), and S.Z. Samadi (environmental engineering). His team has developed influential methods in functional regression and influential curve detection.
Teaching:
Hitchcock teaches advanced statistics courses such as Bayesian Data Analysis, Multivariate Statistics, and Time Series Forecasting. Recent courses include STAT 542 (Computing for Data Science) and STAT 530 (Applied Multivariate Analysis).
Student Advising:
Guided PhD students in topics like functional clustering, stock price prediction, and music genre analysis. Notable advisees include Zizhen Wu (functional registration), Shan Zhong (deep learning ensembles), and Aimée Petitbon (multinomial time series).
