Data Science Masters students tackle the mental health crisis and more at the Spring 2020 DATS Presentation

Written by Ebonee Johnson This year’s Spring 2020 DATS Presentation featured a wide variety of insightful and relevant topics. Below, you’ll find a list of the presenters, in addition to some project goals and key takeaways. “A hierarchical bayesian approach for tagged playlist generation” Presenter: Anish JainAdvised by: Eric BradlowConclusion: Read more

By Ally Moraschi, ago

Foundations of Adaptive Data Analysis

Classical tools for rigorously analyzing data make the assumption that the analysis is static: the models to be fit, and the hypotheses to be tested are fixed independently of the data, and preliminary analysis of the data does not feed back into the data gathering procedure. On the other hand, Read more

By Zack Ives, ago

Measuring the World’s Well-Being

The World Well-Being Project (WWBP) is pioneering scientific techniques for measuring psychological well-being and physical health based on the analysis of language in social media. As a collaboration between computer scientists, psychologists, and medical researchers, we are shedding new light on the psychosocial processes that affect health and happiness and Read more

By Zack Ives, ago

Facilitating Trustworthy Data Science

When a data analysis result is published or shared, how do we know whether it is trustworthy?  Conceptually, we must show that each step of the analysis (and each set of parameters used in the step) was justified, and that the original data was itself trustworthy. A team of Penn Read more

By Zack Ives, ago