Daniel S Malinsky

Daniel Malinsky is Assistant Professor of Biostatistics at Columbia’s Mailman School of Public Health. His methodological research focuses mostly on causal inference: developing statistical methods and machine learning tools to support inference about the consequences of (e.g.) medical decisions, environmental & social exposures, and policies. Application areas of particular interest include environmental determinants of health (especially air pollution) and health disparities. Dr. Malinsky also studies algorithmic fairness: understanding and counteracting the biases introduced by data science tools deployed in socially-impactful settings. Finally, Dr. Malinsky has interests in the philosophy of science and the foundations of statistics.

Daniel Malinsky serves as an Advisory Committee Member.