Dr. Sinead Williamson

Biography

Sinead Williamson joined the University of Texas at Austin in 2013. She is a senior research scientist at Amazon, Inc. and a lead machine learning scientist at CognitiveScale. Her main research focus is the development of nonparametric Bayesian methods for machine learning applications. In particular, she is interested in constructing distributions for correlated measures of complex structures and modeling structured datasets that exhibit spatio-temporal dependence. This includes models for documents where the topical composition varies over time and for temporally evolving social networks. A key objective of her research is to create efficient inference algorithms for these models, and she is currently investigating methods that allow the application of Bayesian nonparametric techniques to large datasets. Sinead is also a board member of Women in Machine Learning.

Research Interests

Experience