The Center for Statistics and Applications in Forensic Evidence (CSAFE) has added two more webinars to the spring webinar series. The webinars, which will both be in May, will focus on footwear examiner performance and algorithms in forensic science.
The webinars are free and open to the public, but researchers, collaborators and members of the broader forensics and statistics communities are encouraged to attend. Each 60-minute webinar will allow for discussion and questions. To register, visit https://forensicstats.org/events.
Topics and Dates
Assessing Footwear Examiner Performance: Randomly Acquired Characteristic (RAC) Examinations
May 13, 11 a.m.–Noon CDT
Department of Statistics, University of California, Irvine
The collection of footwear evidence is a difficult and time-consuming process. The analysis of the evidence can play an important role in criminal proceedings. As with other pattern-matching disciplines, a key question concerns the reproducibility and reliability of forensic footwear analyses. In this presentation, Corey Katz, a graduate researcher at the University of California, Irvine, will discuss the reliability of footwear examiners when it comes to one particular aspect of the examination process—identification of randomly acquired characteristics. Katz will discuss a statistical model adapted from brain imaging as it applies to understanding the performance of examiners and introduce a new hierarchical model to better estimate examiner performance across different impressions.
Algorithms in Forensic Science: Challenges, Considerations and a Path Forward
May 25, Noon–1 p.m. CDT
School of Criminal Justice, Forensic Science Institute, University of Lausanne, Switzerland
Calls for stronger scientific foundations supporting the interpretation of forensic evidence have been made for well over a decade. Over the years, several probabilistic and statistical methods have been introduced; however, many practitioners within the forensic science community—particularly those in the pattern and impression evidence disciplines—have been reluctant to apply them operationally. In this presentation, Henry Swofford, a doctoral candidate at the University of Lausanne, will explore why practitioners are generally in opposition to algorithmic interventions and how their concerns might be overcome.
For more information, read Swofford’s recent publication, Implementation of algorithms in pattern & impression evidence: A responsible and practical roadmap. It is available at https://www.sciencedirect.com/science/article/pii/S2589871X21000103.