Dare to Do It
Raphaëlle Delpont, always wanted to pursue a technical degree in data science so she could bridge the gap between research and industry. Read more about how she navigated gender bias and her journey to MIT Sloan.
Raphaëlle Delpont, always wanted to pursue a technical degree in data science so she could bridge the gap between research and industry. Read more about how she navigated gender bias and her journey to MIT Sloan.
With vaccine rollouts projected to take many months, and a new, more contagious strain of the coronavirus appearing around world, gasping economies are desperately in need of their own shot in the arm.
Almost everyone wants to do something about climate change, but it is challenging to know what levers to pull to make real change. Simulations may be the key to finding the answer.
Some of the most tragic ferry accidents in recent years have been the result of pilot error. Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have found a solution—remove the pilot. Their new autonomous vessel, Roboat II, relies on algorithms, similar to those in ...
The name Angela Davis has been synonymous with radical activism since the 60s. In the intervening years, Davis has channeled those efforts for change into an equally impactful academic career. Now 76, she is a professor emerita at the University of California, Santa Cruz and the author of several in...
Online shopping is even more popular now because of the pandemic. Buyer beware: Product rankings can be based on fraudulent data like fake clicks, purchases, and reviews.
Jorge Arbesú-Cardona, SFMBA ’18, spoke to India Lab students in early March about what he called the "magic of Action Learning."
After graduating from the MIT Sloan School of Management, classmates Shayna Harris, MBA '11, and Noramay Cadena, LGO '11, set off on their own varied career paths in food and supply chain operations, aerospace engineering, and venture capital.
The Covid-19 pandemic is forcing people around the world to cope with much higher levels of uncertainty than most of us have ever confronted.
In the early days of big data, organizations invested heavily in analytics talent, data platforms, and business intelligence units in the hopes of making key business activities better, cheaper, and faster. The majority of these efforts were for internal consumption only and had no direct value for ...