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Algorithms are ubiquitous: they track our sleep, help us find cheap flights, and even help us see black holes. However, designing novel algorithms is extremely difficult, and we do not have efficient algorithms for many fundamental problems. The goal of my research is to accelerate algorithm discovery by building an automatic computer scientist. To work towards this goal, my research focuses on inductive logic programming, a form of machine learning in which my collaborators and I have demonstrated major advances in automated algorithm discovery over the past five years. In this talk and paper, I survey these advances.