New Faculty Spotlight: Carlos Cinelli

What is your Research Focus?

Cinelli’s research focuses on developing new theory, methods, and software to help data scientists make reliable causal inferences under realistic settings – more specifically, many of these tools enable empirical scientists to assess the robustness of their scientific findings against plausible violations of traditional assumptions. He is particularly interested in the inferential challenges faced by social and health scientists, as well as the intersection of causality with machine learning and artificial intelligence. His work has resulted in publications in the most prestigious outlets of statistics, epidemiology and machine learning. Most notably, these results are having a real impact in research practice and have been applied by many scientists across different disciplines, ranging from economics, political science, neurodevelopment, epidemiology and genetics.

What opportunities at the UW excite you?

One super exciting aspect of UW is its strong interdisciplinarity. Two of my current projects consist of: (i) continuing the development of theory and software to make sensitivity analysis easy to perform routine and standard practice across the empirical sciences; and, (ii) developing the foundations for a more flexible approach to causal inference with credible assumptions. Initiatives such as the Center for Statistics and the Social Sciences, as well as the strong connections of Statistics with other departments such as Biostatistics and Computer Science provides an invaluable environment towards achieving this goal.