Fragment screening is increasingly used in early-stage drug discovery, but designing efficient campaigns is a difficult and open problem. I hope to improve this efficiency, initially by using machine learning methods, such as convolutional neural networks, to more accurately predict protein-ligand and protein-fragment interactions. Subsequent work will include developing active learning techniques to better inform experimental decision making.