UVA’s PhD in Statistics offers comprehensive training in probability theory, statistical inference, and the development of new methodologies for complex data. Students pursue advanced research in Bayesian analysis, high-dimensional modeling, statistical learning, and applications across medicine, business, AI, and the environment. Graduates become leaders in academia, government, and industry.
Bayesian hierarchical modeling of climate variability in long-term weather prediction
Development of shrinkage estimators for high-dimensional genomics data
Nonparametric density estimation for online recommendation systems
Asymptotic properties of deep neural network estimators
Gibbs sampling improvements for complex posterior distributions
Sequential Monte Carlo methods for dynamic systems modeling
Sparse covariance matrix estimation in financial risk forecasting
Functional data analysis in wearable health sensor outputs
Extreme value theory applications in natural disaster insurance modeling
Theoretical advances in empirical likelihood methods
Random forests for high-throughput screening in drug discovery
Bootstrapping techniques in spatial statistics for ecological modeling
Stochastic calculus models in option pricing under uncertainty
Optimization of decision rules under false discovery rate control
Semi-supervised learning for rare event classification in fraud detection
Graph-based statistics for social network anomaly detection
Markov chain convergence analysis in latent variable models
Adaptive experimental design in biomedical trials
Shape the future of data-driven science with UVA’s cutting-edge PhD in Statistics.
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