Ph.D. Program Poster Session

Ph.D. students in their 4th year and above will present their research illustrating their methods and outcomes. 

Bayesian Nonhomogeneous Hidden Markov Models to Leverage Routine in Physical Activity Monitoring with Informative Wear Time
Beatrice Cantoni

Martingale Posterior Distributions for Log-concave Density Functions
Fuheng Cui

Applications of Deep Learning in Complex-Valued Signal Processing
Amber Day

Spatially Aligned Random Partition Models on Spatially Resolved Transcriptomics Data
Yunshan Duan

Predictive Coresets
Bernardo Flores Lopez

Bayesian Approaches for Geometric and Dynamic Network Embedding
Yiwei Gong

Avoiding the Surrogate Paradox: An Empirical Framework for Assessing Assumptions
Emily Hsiao

A General Framework to Assess Complex Heterogeneity in the Strength of a Surrogate Marker
Rebecca Knowlton

Exploring Effect Heterogeneity from a Get Out The Vote Intervention Using Bayesian Causal Forests
Anna Morgan

Bayesian Hidden Markov Random Partition Fields for Local Inference on Graphs with Applications in Neuroimaging
Blake Moya

Summarizing Bayesian Nonparametric Mixture Posterior – Sliced Optimal Transport Metrics for Gaussian Mixtures
Khai Nguyen

Spatial Hyperspheric Models for Compositional Data
Michael Schwob

Estimating Heterogeneous Treatment Effects with Bayesian Nonparametric Quasi-Likelihood
Angela Ting