PhD, Political Science (2016)
Predoctoral Fellow, Quantitative Social Science Initiative (2014-15)
Affiliate, Big Data Social Science IGERT
Data Scientist, Verisk Maplecroft (2015-)
Ben's research at Penn State dealt with quantitative methods for forecasting political instability.
He is currently a Data Scientist with Verisk Maplecroft, where he leads development of predictive models for a range of supply chain disruption events using time series and machine learning models. Topics include large scale events, such as interstate conflict, as well as factory-specific events like labor violations. He also assists in development of automated processes for event capture and index scoring using using text data and natural language processing.