Current: Capstone
Correcting Biases in Neuroimaging Data Analysis with R.

(Completed: Summer 2022). Probabilistic clustering of complex biomarker data for Alzheimer’s Disease. Position after graduation: Analyst for Amazon.

(Completed: Master’s Thesis, Spring 2023). Compensating for selection bias when detecting altered functional connectivity in autism. Position after graduation: PhD student in the Department of Biostatistics at Brown University.

(Completed: Capstone, Spring 2023). Flexibly modeling motion confounders in functional connectivity studies with an application to autism.

(Completed: Spring 2020). Improved Algorithm for Independent Component Analysis (ICA) with Relax and Split Approximation. Position after graduation: PhD student in the Department of Statistics at the University of South Carolina.

(Completed: Spring 2020). The impact of quality control exclusion criteria on functional connectivity in children with neurodevelopmental disorders. Position after graduation: Statistical programmer for Novartis.

(Completed: Spring 2019). The impact of initialization in optimization of independent components in functional magnetic  resonance imaging. Positions after graduation: PhD student in the Department of Biostatistics and Data Science at UT Health, the University of Texas.

(Completed: Spring 2018). An exploration of time series models and their application to functional magnetic resonance imaging. Recently completed his PhD student in the Department of Statistics at Rice. Currently at Wells Fargo.