Data-driven learning for dynamical systems in biology 

Essays on high-dimensional econometric models 

Shrinkage methods for big and complex data analysis 

Texture processing for image/video coding and super-resolution applications 

Learning multi-annotator subjective label embeddings 

Analytical and experimental studies in modeling and monitoring of uncertain nonlinear systems using data-driven reduced‐order models 

The role of individual variability in tests of functional hearing 

Differentially private learned models for location services 

Bayesian hierarchical models in genetic association studies 

Integrative analysis of multi-view data with applications in epidemiology 

Feature and model based biomedical system characterization of cancer 

Green image generation and label transfer techniques 

Parametric and non‐parametric modeling of autonomous physiologic systems: applications and multi‐scale modeling of sepsis 

The impact of statistical method choice: evaluation of the SANO randomized clinical trial using two non-traditional statistical methods 

Large scale inference with structural information 

Two-step study designs in genetic epidemiology 

Learning shared subspaces across multiple views and modalities 

Macroeconomic conditions, systematic risk factors, and the time series dynamics of commercial mortgage credit risk 

Integrating annotator biases into modeling subjective language classification tasks 

Tensor learning for large-scale spatiotemporal analysis 

Sparse feature learning for dynamic subsurface imaging 

Noise benefits in expectation-maximization algorithms 

Perspectives on drought and temperature variability for the southwestern United States from a new hydro-isotopic network 

Structure learning for manifolds and multivariate time series 

Modeling and regulating human interaction with control affine dynamical systems