Brian E. Perron is a Professor at the University of Michigan School of Social Work, where he has established himself as a leading researcher at the intersection of data science and social work practice. His academic journey includes a PhD in Social Work from Washington University (2007), an MSW from the University of Wisconsin (1998), and a BA in Psychology from The College of St. Scholastica (1995). Currently teaching courses including Data Visualization Applications, Quantitative Methodologies for Socially Just Inquiry, and Project and Program Design through Spring/Summer 2025, he maintains an active presence in both classroom instruction and cutting-edge research. Dr. Perron's research interests focus on service research, data science, artificial intelligence applications in social work, and non-profit data consulting. He has developed expertise in helping community-based organizations implement data management systems and create interactive visualizations for non-technical users. His work with the Child & Adolescent Data Lab examines services for vulnerable youth and families in the child welfare system. Notably, he has become a pioneer in exploring the ethical application of AI tools like machine learning and natural language processing within social work contexts, publishing extensively on retrieval-augmented generation systems, word embeddings, and API integration for social work research. His publication record reveals a significant shift toward AI integration in social work, with 12 of his 15 most recent articles (2023-2025) focusing on artificial intelligence applications. These works demonstrate his leadership in developing practical AI tools for social workers while addressing critical ethical considerations. His research spans child welfare systems, substance abuse, mental health services, and educational curriculum development, with particular attention to racial disparities and data privacy concerns in vulnerable populations. Among his scientific achievements, Dr. Perron received an award from Casey Family Programs and has secured research funding from the National Institutes of Health, Department of Veterans Affairs, and the state of Michigan. His work on prenatal cannabis exposure and child maltreatment has generated significant policy implications, particularly regarding racial bias in newborn drug testing practices. As an educator, Dr. Perron specializes in making research and data analysis accessible to students without strong math backgrounds while also teaching diagnosis and treatment of mental health and substance use disorders. He maintains his expertise through continuous learning, including participation in MOOCs to stay current with technological developments. His work with the Child & Adolescent Data Lab represents a significant institutional contribution to improving service outcomes for vulnerable youth through data-driven approaches.








