Sharlee Climer

The paper uses exascale computing to generate high-resolution global geoclimate zones by clustering environmental similarity data from 71 variables over 50 years.

The paper identifies high-resolution environmental zones and predicts longitudinal climatic processes using vector comparison and network analysis methods.

The paper identifies structural variants (SVs) in ASD families and links them to molecular pathways and genes associated with non-verbal ASD, using explainable AI for subgroup identification.

The paper introduces Maestro, a network analysis method that identifies synchronized genetic activities in Alzheimer's disease, finding a pattern associated with AD that is significantly more common in cases than controls.