Neumann’s research revolves around the application of machine learning to text, audio and image data in the social sciences, in particular in political advertising. His teaching interests at Duke Kunshan include machine learning and statistics.

His research has been published in journals such as Computational Communication Research, the Journal of Information Technology & Politics, and the Journal of Artificial Societies and Social Simulation.

He has B.A. and M.A. degrees in political science from the University of Mannheim, Germany, and a Ph.D. in Political Science and Social Data Analytics from Penn State University. He served as a post-doctoral researcher at Wesleyan University and the Wesleyan Media Project from 2020 to 2023.