Daniel Cannon, Data Scientist
Daniel uses machine learning and statistics to transform mountains of data into useful knowledge to advance Innovate + Educate's mission of discovering opportunities for unemployed and underemployed Americans.
Daniel received his Master's of Science and Bachelor's of Science in Computer Science from the University of New Mexico. As a member of the Complex Adaptive Systems of Systems group at Sandia National Laboratories, Daniel developed software to model the spread of infectious diseases, simulate public policy interventions, and provide guidance to US policy makers. Daniel later joined the Translational Informatics Division of the UNM Health Sciences Center where he used machine learning to derive predictive models of neonatal sepsis using protein biomarkers and developed tools to discover novel drug targets by piecing together knowledge mined from academic publications.