Fighting Poverty with Data: Research at the Intersection of Machine Learning and Global Development

In wealthy nations, improved algorithms and new sources of “big data” are creating exciting opportunities for commercial profit and academic research. In developing economies, however, fewer sources of robust data exist, and it remains unclear if and how the world’s poor will benefit from new approaches to data science. In this talk, Dr. Blumenstock will discuss ongoing work that capitalizes on recent advances in machine learning to tackle some of the problems affecting poor and marginalized populations. This talk will focus on recent results from Afghanistan, Indonesia, and Rwanda, which illustrate how large-scale data from mobile phone and satellite networks can be combined with on-the-ground experiments and surveys to better understand the causes and consequences of global poverty. Throughout, I will highlight open technical research questions where the right computer scientist or statistician has the opportunity to make a lasting real-world impact.

The Berkeley Distinguished Lectures in Data Science, co-hosted by the Berkeley Institute for Data Science (BIDS) and the Berkeley Division of Data Sciences, features faculty doing visionary research that illustrates the character of the ongoing data, computational, inferential revolution.  In this inaugural Fall 2017 "local edition," we bring forward Berkeley faculty working in these areas as part of enriching the active connections among colleagues campus-wide.  All campus community members are welcome and encouraged to attend.  Arrive at 3:30pm for tea, coffee, and discussion.