May 19, 2017
Finding clean energy solutions is no easy feat. Recently, some of Silicon Valley’s sharpest data science minds came together to use their powers for good at the U.S. Department of State’s Clean Energy Data Science Challenge, co-hosted by Booz Allen Hamilton, the World Bank and Galvanize San Francisco, to develop solutions for those without access to reliable electricity.
According to the World Energy Outlet over 1.2 billion people around the world lack access to reliable electricity in 2016. The objective of the Clean Energy Data Science Challenge was to mine and leverage open data to promote the development of innovative and scalable solutions.
There were 15 companies who presented with solutions to address global problems around energy; of those companies, three active students and an alumnus of the University of New Haven-Galvanize Master of Science in Data Science program, and two current students in the Galvanize Data Science Immersive program also participated.
The winning team created a mock startup called Cartesian Product, a clean energy knowledge management platform that enables a diverse set of users to identify high-potential emerging energy markets. The vision is to crowdsource the collection of ground-truth data to domain experts, enabling machine learning solutions that optimize alternative energy investment on a global scale.
As Zvika Krieger notes in her Medium article about the Challenge, “Providing access to energy can enable progress across education, health, social and economic sectors” in the developing world and beyond.
We’re grateful to have access to reliable electricity, and to be working with and learning from dynamic people who are applying their ingenuity and expertise to helping others gain access to a resource that is often taken for granted.
Read more about startups addressing global issues at Tech.Co
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