Lubricants And Glitter: Revolutionizing Sexual Assault Investigation

Tuesday, March 2nd, 5 PM PST

Dr. Candice Bridge, Associate Professor of Chemistry at the University of Central Florida and the National Center for Forensic Science

There’s still time to register for this Zoom event.

Sexual assaults are an unfortunate reality in modern society, which includes situations in which the assailant is known or unknown. While DNA is the go-to forensic evidence in sexual assault cases, the reality is that the use of condoms in sexual assault is increasing in an effort to minimize the type of DNA left at the crime scene, specifically sperm/semen. Therefore, in the absence of DNA, it is necessary to identify other type of forensic evidence (such as lubricants and cosmetic residues) that could be used in these types of cases to link the three points in the criminal triangle, e.g. victim, suspect and crime scene. This talk will discuss current efforts that we are conducting to understand the evidentiary value of lubricant and cosmetic evidence and appropriate analytical methods to analyze and characterize unknown samples collected in a sexual assault or physical assault cases.

Dr. Candice Bridge is an Associate Professor in the Department of Chemistry and the National Center for Forensic Science. She received her Ph.D. in Analytical Chemistry from the University of Central Florida. Dr. Bridge was a postdoctoral associate at the Center for Research and Education of Optics and Lasers at UCF before joining the Department of Chemistry faculty at Howard University. She then worked at the U.S. Army’s Defense Forensic Science Center as a Forensic Scientist and then a Research Scientist before joining UCF. Her current research focuses on the analysis of trace evidence forensic materials to understand the uniqueness of chemical features. Using a variety of mass spectrometry techniques, they look to develop analytical methods that can increase the validity and evidentiary value of forensic evidence, which is determined using chemometric statistical techniques.