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A. Haensch, Becoming a Data Scientist: An Impractical Guide, The American Mathematical Monthly, 132(1), 6-13, 2025.
- * J. W. Bourgeois, A. Haensch, S. Kher, D. Knox, G. Lanzalotto, T.A. Wong, How to Use Causal Inference to Study Use of Force, CHANCE, 37:4, 6-10, 2024.
- C. Kelling, A. Haensch, A. Mendible, S. Brooks, A. Wiedemann, M. Aminian, W. Hasty, J. Higdon, Data Collection and Analysis for Small-TownPolicing: Challenges and Recommendations, Statistics and Public Policy, 2024.
- A. Haensch, D. Gordon, K. Knudson, J. Cheng, A Multi-Method Data Science Pipeline for Analyzing Police Service, The American Statistician, 1-18, 2024.
- * C. Börgers, N. Dragovic, A. Haensch, A. Kirshtein A Particle Method for Continuous Hegselmann-Krause Opinion Dynamics. In Complex Networks & Their Applications XII (pp. 1-13). Springer Nature Switzerland AG. 2024.
- A. Haensch, E. Tronci, B. Moynihan, B. Moaveni, Regularized Hidden Markov Modeling with Applications to Wind Speed Predictions in Offshore Wind, Mechanical Systems and Signal Processing, Vol. 211, 2024.
- * C. Börgers, N. Dragovic, A. Haensch, Political Centrism and Extremism: A Mathematical Analysis, SIAM News Research, Jan. 2024.
- * C. Börgers, N. Dragovic, A. Haensch, A. Kirshtein, L. Orr, ODEs and Mandatory Voting, CODEE Journal special issue on Engaging the World: Differential Equations Influence Public Policy, Vol. 17, Article 11, 2024.
- * B. Boghosian, C. Börgers, N. Dragovic, A. Haensch, A blue sky bifurcation in the dynamics of political candidates, The American Mathematical Monthly, 131(3), 225-238, 2023.
- A. Haensch, N. Dragovic, C. Börgers, B. Boghosian, A geospatial bounded confidence model including megainfluencers with an application to Covid-19 vaccine hesitancy, The Journal of Artificial Societies and Social Simulations, 26(1) 2023, 8.
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