Current Students
Current Students
Joshua Pearcy (Ph.D.): A Bayesian Approach to Infer Changes in Disease Transmission.
Ph.D.
Shangyuan Ye (2018): "Bayesian analysis for sparse functional data". Assistant Professor, Florida International University.
Ru Wang (2021): "Bayesian finite mixture modeling for classifying electronic health records with applications on diabetic retinopathy prediction". Senior Advisor of Data Science, Dell.
Shiteng Yang (2021): "Maximum likelihood estimation under efficient importance sampling for nonlinear state space models". Data Scientist, Amrock.
Laura Lartey (2023): "Monitoring spatio-temporal trends in COVID-19 using state-space SEIR models". Quantitative Analytics Specialist, Wells Fargo.
Siyu An (2024): "Bayesian modeling and prediction for the time-to-terminal event with unaligned longitudinal observations in electronic health records." Clinical Professor, Oklahoma City University.
M.S.
Longji Sun (2016): "Bayesian nonparametric spatial modeling for Mesonet data using Dirichlet process mixing".
Ru Wang (2017): "Hamiltonian Monte Carlo for the item response theory model with an application to judicial accomplishment measurement".
Youngjun Chae (2018): "A simulation study for coherence estimation of time series".
Jiacheng Huang (2019): "Cross-sectional regression and predictor selection for financial data in China stock market".
Xijia Han (2021): "Bayesian spatio-temporal modelling for soil moisture data using splines".
Ting-Yao Lee (2025): "Literature Review on Neural Networks from a Bayesian perspective".
B.S.
Derek Wietelman (Honors, Wentz Scholar, 2015): "A Bayesian analysis of Carbon Dioxide emissions in states under the Regional Greenhouse Gas Initiative".