Callie Federer is the Director of Data Science at DAT, focused on machine learning research and development. Before DAT, she developed machine learning algorithms such as forecasting, computer vision and natural language processing across various fields including particle accelerators, cancer treatment, education and programmatic advertising. She has a computer science degree and a PhD in Computational Bioscience focusing on the intersection of machine learning and neuroscience with her thesis: “Putting more ‘Neural’ into Artificial Neural Networks”. She was awarded the NSF Graduate Research Fellowship which fully funded her thesis work.