Research interests: Designing and modeling gene drive systems, which enable a genetic payload to spread through a population even when imposing a fitness cost on its host organism. He is interested in novel methods to control vector borne disease and hopes that gene drive will become a cost-effective approach to address this problem.
Keith came to the Kuceyeski Lab from the Human Connectome Project (University of Minnesota), where he created and maintained pipelines for processing their vast database of images. He currently works on extracting brain connectivity measures from MR-imaging in clinical populations, i.e. multiple sclerosis and traumatic brain injury. The extracted imaging biomarkers will then used in quantitative modeling/machine learning approaches to predict impairment and recovery after disease/injury. This work aims to both understand the mechanisms of disease and injury, as well as improve the accuracy of clinical prognoses.