Jacob Schreiber is a fifth year Ph.D. student and IGERT big data fellow in the Computer Science and Engineering department at the University of Washington. His primary research focus is on the application of machine learning methods, specifically deep learning ones, to the massive amount of data being generated in the field of genome science. Additionally, he routinely contributes to the Python open source community as the core developer of pomegranate, a package for flexible probabilistic modeling, apricot, a package for data summarization for machine learning, and in the past as a core developer for the scikit-learn project. Future projects include graduating.