
Justin Miller-Schulze and Smith Purdum explain how machine learning and chemometrics can improve fire debris classification in forensic science applications.

Justin Miller-Schulze is a Professor of Chemistry at Sacramento State University, and an Analytical and Environmental Chemist focused on the development and/or adaption of analytical methodology to quantify chemical tracers in environmental or biological matrices. Current projects in in the Miller-Schulze group include the identification and quantification of volatile organics in additive manufacturing (3D printing) emissions, investigation of the impact of diesel exhaust and/or VOCs on metabolic profile and neurodevelopment using fruit flies as a model organism, and development of automated liquid chromatography mass spectrometry (LC–MS) approaches to measure emerging contaminants in aqueous systems. He earned his Ph.D. in Analytical Chemistry from the University of Washington, Washington, Seattle, USA and his B.S. in Environmental Chemistry from UC San Diego, San Diego, California in 2003.

Justin Miller-Schulze and Smith Purdum explain how machine learning and chemometrics can improve fire debris classification in forensic science applications.