For our current edition of “Video Highlights” I’d like to offer this talk that will review a series of recent papers that develop new methods based on machine learning methods to approach problems of ...

Causal inference, at the intersection of statistics and machine learning, is an active field of research that develops methods and algorithms for the data-driven derivation and analysis of ...

The past decade has witnessed significant advances in causal inference and Bayesian network learning, two intertwined disciplines that allow researchers to discern underlying cause‐and‐effect ...

The manufacturing landscape is evolving rapidly, with intelligent systems increasingly promising to boost efficiency, quality, and overall competitiveness. Traditional machine learning (ML) has ...

Data really powers everything that we do. Research activities in the data science area are concerned with the development of machine learning and computational statistical methods, their theoretical ...

Faculty in the Statistical Learning and Data Science Hub advance statistical and machine learning methods tailored to the unique challenges of biomedical and epidemiologic data, including ...

The use of machine learning in statistics production is being explored widely, with applications including coding, outlier detection, and imputing missing values. Relatively little work has so far ...