● Hyperspectral image Analysis ○ Developed novel methods for the detection of germination in barley seeds using 580-dimensional hyperspectral images (images with many color channels, as opposed to the traditional 3), improving on current methods by being faster, easier, non-destructive, and requiring fewer seeds ○ Built a deep neural network with TensorFlow and a gradient boosting model with Catboost to predict barley germination and tuned model performance, reducing error by 46% ○ Built an interactive web app for the visualization of hyperspectral images using Plotly Dash, enabling quick analysis and quality assurance of images taken in the field● Barley RNA analysis ○ Performed gene co-expression analysis on barley RNA data in R that led to publication.