Daniel Hawthorne

Daniel Hawthorne is a seasoned researcher with a solid foundation in cognitive science, holding a Ph.D. from Stanford University. Early experience includes a role as a SULI Research Trainee at Pacific Northwest National Laboratory, where tools were built for knowledge management and expert opinions were integrated into Bayesian networks. As a Graduate Student Researcher at Stanford, Daniel focused on computational models of human behavior, utilizing advanced causal modeling and inference tools. Following academic pursuits, Daniel served as CTO and Co-Founder of Datawallet, leading the development of data sourcing and analysis tools, and contributed as a Research Scientist at Ought, where efforts centered on probabilistic forecasting. At Meta, Daniel advanced from Research Data Scientist to Research Scientist (Machine Learning Engineer), continuing to leverage expertise in machine learning and data-driven research.