Stephen is a Precision Cardiology Lab and Ellinor Lab member who is based in the analytical method development / machine learning research group led by Mehrtash Babadi in the Data Sciences Platform of the Broad Institute of MIT and Harvard, where he is a Machine Learning Scientist I. As a computational method developer in the Ellinor Lab, Stephen works on single-cell RNA sequencing data, and uses machine learning techniques and probabilistic modeling to develop principled approaches to data analysis that can be run on cloud compute architecture. Stephen focuses on developing custom analysis methods for the Precision Cardiology Lab (part of the Broad–Bayer Collaboration) that can also be used by the wider research community as open-source tools. Stephen joined the Broad Institute in June 2018 after receiving his Ph.D. in physics from Harvard University, where he worked on nanopore DNA sequencing experiments as part of the Harvard Nanopore Group. He also has an M.Phil. in physics from the University of Cambridge, where he was a Churchill Scholar in the Physics of Medicine program, in addition to B.S. degrees in physics and biochemistry, both from Case Western Reserve University.