Daniel Malinsky

Daniel Malinsky serves as an Assistant Professor of Biostatistics in the Mailman School of Public Health at Columbia University. His institutional affiliations include:

• Foundations of Data Science Center (Affiliated Member)
• Health Analytics Center (Affiliated Member)
• Computational Social Science Committee

His research centers on causal inference, developing statistical and machine learning methodologies for estimating treatment effects, interventions, and policy impacts using graphical models such as DAGs and Bayesian networks. Current projects span causal discovery (structure learning), semiparametric inference, time series analysis, and missing data handling. He also investigates algorithmic fairness to mitigate biases in data-driven decision systems deployed in socially consequential domains, complemented by scholarly interests in statistical philosophy and foundational theories.

No information regarding student advising, grant funding, or dedicated laboratory infrastructure was provided in the source materials.