ASCLD Forensic Research Committee Lightning Talks text with lightning and ASCLD logo.

An upcoming episode of the ASCLD Forensic Research Committee (FRC) Lightning Talks will include a presentation from Alicia Carriquiry, the Center for Statistics and Applications in Forensic Evidence (CSAFE) director.
The virtual episode will be held Thursday, August 21 at 1 p.m. EST, focusing on machine learning in forensics.

Alicia Carriquiry
Alicia Carriquiry

The ASCLD FRC Lightning Talks highlight new and emerging research in all areas of forensic science. Each episode features three short talks given by practitioners, researchers or students. The August 21 episode will feature presentations from Carriquiry, Agnes Winokur with the ASTM Committee E30 on Forensic Sciences and Gamaliel Rose from the DEA Statistical Services.

Carriquiry will present “Machine Learning for Drug Profiling: Keeping it Interpretable is a Good Goal.” Her talk will discuss how deep learning methods can be effective at extracting information from data, but at the cost of transparency. Using chemometrics data for illustration, Carriquiry will show that interpretable machine learning algorithms can be accurate and result in reproducible findings that are simple to interpret.

Winokur will present “Building the Blueprint: Consensus-Based Standards for Machine Learning in Forensics.” Her talk will highlight standard-developing efforts of AI and machine learning consensus-based standards, both existing and future.

Rose’s presentation, “Beyond Algorithms: Why Data Matters Most,” will explore what data considerations can affect the success of machine learning applications in forensic science, including data quality, representation and bias mitigation.

For more information about the ASCLD FRC Lightning Talks, visit www.ascld.org/forensic-research-committee/frc-lightning-talks.

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