Presentations

Our presentation, Modeling Firearm Injury Risk Using Spatial Random Forests, will be delivered by Dr. Gia Barboza-Salerno at the Women in Statistics and Data Science on November 12, 2025 in Cincinnati, OH.

This new article by Dr. Gia E. Barboza-Salerno argues that Predictive Risk Models (PRMs) can be effective when focused on prevention.

Presented at the 2025 National Research Conference for the Prevention of Firearm-Related Harms, this study develops a remote-sensing–based framework to identify built environment risk factors for firearm injury in Cook County, Illinois.

Congratulations to our undergraduates Oliva McLucas and Malcolm McCarthy for their abstracts accepted to the 2025 GIS Day at The Ohio State University on November 19, 2025.

Our presentation, Enhancing Brain Injury Surveillance Using Large Language Models and Topic Modeling, was delivered by Dr. Shockley McCarthy at the AI for BI Conference at The Ohio State University on October 17, 2025.

Dr. Barboza-Salerno addresses the Grand Challenge to Prevent Gun Violence in a feature by the College of Social Work.

Presented at the ISPCAN World Congress on Child Abuse and Neglect, Melbourne, Australia, August 2426, 2026. Full title: Detecting Hidden Mechanisms of Abuse-Related Injury in Children: Structured Topic Modeling of Clinical Death Reviews and Legal Opinions Triangulating Multidisciplinary Child Fatality Reviews with Factual and Procedural Narratives from Case Law

Presentation at the American Educational Research Association (AERA) Annual Meeting Date: Saturday, April 11, 2026 Time: 9:45 AM to 11:15 AM PDT (12:45 PM to 2:15 PM EDT)

Applying Social Geography to Structural Mitigation in Capital Defense Summary: This project applies social geography and spatial data analysis to strengthen structural mitigation arguments in capital defense.

In progress Real Help–Real Hope: Where Do We Go From Here? A Community-Based Approach to the Opioid Crisis Summary: This keynote presentation, delivered at the Opioid Treatment Providers of Georgia conference, highlights the need for a comprehensive, public health–centered response to the opioid crisis.

This study applies spatially explicit machine learning to model non-fatal shootings across Chicago census tracts from 2020 to 2024. A curated set of predictors was compiled, including measures of social and environmental vulnerability, the built environment, and housing inequality.

Our work on the socio-physical and natural enviornment was presented at the ISPCAN 2024 international conference. No previous research has comprehensively examined how different aspects of the sociophysical and built environments increase child abuse and neglect (CAN) risk.

In progress A Novel Integration of Social, Perceptual, and Built Environmental Data Integrating AI, Deep Learning, and Spatial Analytics to Investigate Environmental Correlates of Child Neglect

Our work on Utilizing AI-Driven Technology and Geospatial Analysis to Explore Landscape Morphology, Social Vulnerability, and Child Neglect in Los Angeles will be presented at ISUF 2025 in Torino, Italy.