While travelers are sprinting to tight connecting flights, airports are scrambling to make predictions. Visiting Associate Professor Yael Grushka-Cockayne, alongside Heathrow Airport and researchers at University College London, recently built and demoed a machine learning model that removes the guesswork.

Responsible innovation is the name of the game. Giovanni Buttarelli, head of the European Data Protection Supervisor, calls for defining global digital ethics standards and broad input — not just from engineers, but also from the humanities and social sciences — to get there.

You heard correctly. Target is successfully navigating the “retail is dead” — or at least drastically evolving — era. Professor Srikant Datar’s recent case study unpacks how Target went from data rich, but insights poor to lucratively leveraging the information it was collecting. You could say, Target’s in the retail and data business now.

How do we know if social enterprises and impact investors are actually improving low-income consumers' lives? We listen. Or at least, Acumen’s Lean Data team does. So far, they’ve had conversations with over 70,000 people in 27 countries to help inform future investment decisions.

While satellites may be some of our most impressive technology, they are bogged down by a single bottleneck — data. Satellites orbiting Earth routinely struggle to relay data back down to Earth in a timely manner, with sizable implications for the real world, on the ground economy. This is why companies like Analytical Space are hoping to tap into the big data space revolution that is just waiting to happen.

Machine learning is a popular topic in most industries these days, and it will come as no surprise that this is true for astronomy and astrophysics as well. University of Colorado PhD student Avery Schiff explores how a deep learning algorithm is being used to classify galaxy morphologies in this article from graduate student astronomy journal Astrobites.

It’s a declaration we’ve all heard before: “We need more collaboration! We need to break out of our silos and build integrated, cross-functional teams!” But what if — when it comes to collaboration — there can be too much of a good thing? This is the hypothesis Professor Jeff Polzer set out to test with his research on collaborative overload, that is how the amount of collaboration relates to organizational productivity. Using digital trace data to analyze organizational productivity at scale, Professor Polzer finds some answers that may surprise you.

Fresno Unified School District had built a robust data-collection system, but none of it was being put to use. That is, until Harvard Strategic Data Project Fellow David Jansen developed a app that turned improving student outcomes into a compelling game.

Women are more likely than men to drop out of data science classes when they receive a low score in an early assignment. The Coursera team shares how they’re using targeted interventions to tackle this trend and help close the gender gap in STEM.

As the largest online learning platform for higher education, Coursera has global scale. In this flash talk from our 2018 Future Assembly, Head of Data Science Emily Glassberg Sand shares how she and her team of data scientists harness data from millions of participants to enhance learner outcomes and deliver personalized, targeted recommendations on everything from suggested courses to difficult problems.