Caitlin's forensic research focuses on improving fingerprint data storage and analysis through AI. She is exploring how machine learning can streamline the identification process and uncover patterns that traditional methods might miss. Alongside this digital work, she explored latent prints hands-on: on paper and cornstarch-print transfers across various surfaces. This exploration led to a better understanding of the practical challenges of evidence collection. What drives this work is a deep fascination with how fingerprinting works and a desire to make it more accessible, efficient, and reliable, whether through smarter tools or alternative techniques that expand what's possible in the field.