معرفی
Susan VanderPlas is an Associate Professor in the Department of Statistics at the University of Nebraska-Lincoln, with research focusing on statistical graphics perception and computer vision applications in forensic image analysis. She maintains a significant collaboration with the Center for Statistical Applications in Forensic Evidence (CSAFE) at Iowa State University, developing statistical methodologies for bullet, cartridge, and footwear examination.
Her research integrates Forensic Statistics, Statistical Graphics, Computer Vision, Human Perception, Machine Learning, and Statistical Computing to address critical gaps in forensic science and data visualization. She investigates perceptual biases in graphical representations, designs experimental frameworks for visual inference, and creates automated tools for forensic image comparison, bridging cognitive psychology, statistics, and computer science to enhance evidence reliability and data communication practices.
Analysis of her recent publications reveals a cohesive research trajectory emphasizing visual inference for forensic applications and statistical graphics. She has pioneered methodologies for logarithmic scale perception, change point detection via visual lineups, and computer vision diagnostics for residual plots. Her forensic work critically addresses methodological flaws in firearm comparison studies, hidden multiple comparisons inflating error rates, and validation pipelines for cartridge case matching algorithms.
No scientific awards were mentioned in the provided information.
Information about students and grant funding was not specified in the available text.
As a core collaborator with CSAFE—a NIST-funded center—she contributes to interdisciplinary teams developing statistically valid methods for forensic pattern evidence. Her projects focus on algorithm validation for bullet/cartridge matching, uncertainty communication in forensic conclusions, and establishing scientific foundations for toolmark and footwear analysis, directly impacting forensic laboratory practices and legal admissibility standards.
