My work

I am independently developing CaseLinker, a research-driven project focused on grouping and visualizing statistical and contextual information across child exploitation cases. This project was motivated by challenges I encountered with understanding child exploitation cases, including fragmented data sources, difficulty performing cross-case and longitudinal analysis, and the emotional impact of repeatedly reading and processing highly disturbing case material.

CaseLinker aims to address these challenges by serving as a tool for case analysis, enabling researchers, law enforcement, and advocacy organizations to better understand the landscape of child exploitation.

Emphasis on

• Clustering and linking cases based on shared characteristics such as victim context, technologies used, and law enforcement actions

• Visualization of cases with careful, respectful presentation of sensitive content and pattern analysis across investigations

• Statistical analysis of cases and broader child exploitation trends over time

This work is on going and will be updated periodically as my research progresses... Relevant code, experiments, and technical notes are available on GitHub! If you are interested in this work or any related work, have any thoughts on the application of AI to child safety, CSAM / real-world issues, or literally anything else, feel free to reach out!!