Danielle Dean

Danielle Dean

Danielle Dean is a senior data scientist lead at Microsoft in the Algorithms and Data Science group within Cloud and Enterprise, where she leads a team of data scientists and engineers on end-to-end analytics projects that use Microsoft's Cortana Intelligence Suite for applications ranging from automating the ingestion of data to analyzing and implementing algorithms, create web services of these implementations, and integrate them into customer solutions or build end-user dashboards and visualizations. Danielle holds a PhD in quantitative psychology from the University of North Carolina at Chapel Hill, where she studied the application of multilevel event history models to understand the timing and processes leading to events between dyads within social networks.

Webcast: Predictive maintenance meets predictive analytics
June 16, 2016
In a talk aimed at data scientists, students, researchers, and nontechnical professionals, Danielle Dean introduces the landscape and challenges of predictive maintenance applications in the manufacturing industry.