Clarence Worrell is a senior data scientist in the CERT® division of Carnegie Mellon University’s Software Engineering Institute, where he researches data-driven analysis and modeling in cybersecurity. Prior to joining CERT®, he developed applications of machine learning, optimization, and probabilistic simulation for the energy sector. Clarence is also a PhD candidate in industrial engineering at the University of Pittsburgh. His doctoral research surrounds algorithms for spatial variations of classic NP-hard optimization problems, including machine assignment, graph partitioning, and k-center.