Michelle LaMar is a data scientist in the AI Research Labs in the Research & Development division at ETS. Her current research focuses on the application of machine learning and psychometrics to support complex, interactive learning and assessment tasks. She is particularly interested in modeling task-process data using dynamic cognitive models to enable valid inference about multiple layers of student cognition. She received a master’s in curriculum studies from Sonoma State University and a Ph.D. in educational measurement from the University of California, Berkeley. Prior to her doctoral work, she spent 18 years in software engineering, specializing in educational simulations, authoring tools, and natural language parsing.