Balancing Complexity and Utility
"Everything's intentional. It's just filling in the dots." - David Byrne
Knowledge domains in human multi-'omics, electrophysiology, neuroimaging, cognition, and epidemiology have developed alongside computational biology and machine learning to allow for increasingly complex models of psychiatric etiopathology. These high-dimensional models are necessarily complex, but challenging to grasp for non-experts, which often include the knowledge users - the primary health providers, clinical specialists, and policy makers who are not neuroinformaticians. Our group works in this complex space while striving for clarity in our research questions and results.