UVA’s PhD in Data Science integrates mathematical modeling, ethical data practices, and algorithm design for high-impact research. Students explore foundations of ML, causal inference, AI fairness, and scalable computing, producing novel research across domains like healthcare, climate, finance, and education.
Causal modeling for identifying treatment effects in observational healthcare data
Fair classification algorithms with constrained optimization techniques
Graph neural networks for citation prediction and scientific discovery
Differential privacy techniques for secure medical data sharing
Deep generative models for synthetic data generation in sensitive domains
Uncertainty quantification in large-scale forecasting models
Adaptive learning algorithms for online education personalization
Formal guarantees for explainability in black-box ML systems
Meta-learning approaches to cross-domain transfer in predictive models
Trustworthiness metrics for AI models in financial decision-making
Multi-objective optimization in environmental sustainability simulations
Bayesian deep learning applied to autonomous vehicle safety predictions
Causal structure discovery from high-dimensional gene expression data
Computational frameworks for equitable algorithmic decision systems
Shape the ethical, technical, and interdisciplinary future of data science at UVA.
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