Trainees

Coleman Breen’s research focuses on modeling the relationship between genetic sequence variation and DNA methylation.

Bowman Brown’s research focuses on developing explainable AI methods to enable learned models to better support clinical decision making.

Hailey Bussan’s research focuses on how the microbiome influences T-cells during homeostasis and immune challenge.

Emma Croxford’s research focuses on improvements in the development of NLP models that have clinical diagnostic reasoning abilities.

Mason Garza’s research focuses on analysis of the association of HIV infection, the microbiome, meditation, and well-being.

Emma Graham Linck’s graduate research focuses on testing methods for the prediction of individualized treatment effects (ITE) from clinical trials.

Parth Khatri’s research focuses on inferring cell-cell communication through ligand-receptor interactions using single-cell and spatial transcriptomic data in various immunological cases.

Edwin Laboy-Torres’ research focuses on development and application of new tools for analysis of HIV-related proteomics and RNA-protein interactomes.

Da-Inn Lee’s research focus is structure-driven machine learning for 3D genome organization.

John Peter’s research is crafting deep learning foundation models for learning representations of images, with a current focus on fluorescent microscopy.

Spencer Halberg-Spencer’s graduate research focuses on development of computational tools to advance dynamic gene regulatory network inference from single cell omic data for reprogramming and cancer.

Sierra Strutz’s research is focused on the development and optimization of machine learning and deep learning models that predict clinical deterioration among hospitalized children.