#56 Data Science at AT&T Labs Research

This week, Hugo speaks with Noemi Derzsy, a Senior Inventive Scientist at AT&T Labs within the Data Science and AI Research organization, where she does lots of science with lots of data.

They’ll be talking about her work at AT&T Labs Research, the mission of which is to look beyond today’s technology solutions to invent disruptive technologies that meet future needs. AT&T Labs works on a multitude of projects, from product development at AT&T, to how to combat bias and fairness issues in targeted advertising and creating drones for cell tower inspection research that leverages AI, ML and video analytics. They’ll be talking about some of the work Noemi does, from characterizing human mobility from cellular network data to characterizing their mobile network to analyze how its topology compares to other real social networks reported to understanding tv viewership, and how engaged people are in different shows. They’ll discuss what the future of data science looks like, whether it will even be around in 2029 and what types of skills would help you land a job in a place like AT&T Labs.LINKS FROM THE SHOW

DATAFRAMED GUEST SUGGESTIONS

• DataFramed Guest Suggestions (who do you want to hear on DataFramed?)

FROM THE INTERVIEW

• Noemi on Twitter
• Noemi's Website
• Human Mobility Characterization from Cellular Network Data (By Richard Becker et al., Communications of the ACM)
• AT&T Labs Research Website
• NASA Datanauts Website
• Open NASA Website

FROM THE SEGMENTS

Guidelines for A/B Testing (with Emily Robinson ~18:23 & ~36:38)

• Testing multiple statistical hypotheses resulted in spurious associations: a study of astrological signs and health (By Peter C. Austin et al., Journal of Clinical Epidemiology)
• From Infrastructure to Culture: A/B Testing Challenges in Large Scale Social Networks (By Ya Xu et al., LinkedIn Corp)
• Guidelines for A/B Testing (By Emily Robinson)
• 10 Guidelines for A/B Testing Slides (By Emily Robinson)

Original music and sounds by The Sticks.

Episode source