In August of 2017, the American Statistical Association awarded the fifth Causality in Statistics Education Award to Ilya Shpitser, the John C. Malone Assistant Professor of Computer Science.
Established in 2013 to encourage the teaching of basic causal inference methods in introductory statistics courses, the annual award recognizes the work of an individual or team that enhances the teaching and learning of causal inference in introductory statistics coursework. The award provides a $5,000 cash prize each year. In 2018, the $5,000 award was funded by Microsoft Research and Google.
“Even with the recent development of causal inference tools, which are currently sweeping new insights and application areas, most statistics educators and textbooks do not provide any information on these tools,” said Judea Pearl, co-chair of the prize selection committee, in an article announcing Shpitser as the recipient.
Shpitser has developed a graduate-level course for students with a machine learning and data science background. The course combines techniques of graphical and counterfactual models and provides both accessible coverage of the field and conceptual, computational, and project-oriented exercises for students.