Peter Baumgartner, of RTI’s Center for Data Science, combines design thinking and modern data science to ensure that data-driven solutions solve problems, provide insight, and meet the user’s needs. His work spans the domains of criminal justice, law enforcement, public health, agriculture, and sociology. He has published work evaluating the accuracy and bias of pre-trial risk assessments as well as research understanding the public health impact of cannabis dispensaries on social media.
Mr. Baumgartner’s technical focus is natural language processing. He is the founder and project lead of RTI TAP—a text analytics platform that uses natural language processing and data visualization. TAP facilitates research projects using qualitative coding of documents by accelerating the coding process and enabling analysis with semantic network analysis and visualizations. In developing TAP, he takes a user-centered design approach, cycling between collecting feedback from eventual users, integrating new functionality based on their needs, and collecting feedback on new functionality. Mr. Baumgartner is also the lead data scientist on the Arrest Related Deaths (ARD) media review project for the Bureau of Justice Statistics. The ARD data pipeline uses machine learning to filter millions of monthly news articles down to a relevant set of articles for humans to review, helping them to generate more accurate estimates of arrest related deaths in the United States. He has also developed tools to automatically code and visualize open-ended survey responses and used deep learning to build a recommender system for teams of coders labeling academic transcripts.
Before joining RTI in 2015, Mr. Baumgartner worked as a consultant at Deloitte in its Advanced Analytics and Modeling practice. While there, he worked on several analytics initiatives in insurance underwriting, workforce analysis, veteran career services, health care and life sciences, and business development.