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With the explosive growth of Big Data and the Internet of Things, how we efficiently collect and analyze large data sets is a common topic of discussion. However, what if there were a cap on how much data we can physically compute?
Emmanuel Abbe, assistant professor at Princeton University, demonstrated this to be the case in his Bell Labs Prize-winning proposal. Abbe showed that there is a fundamental limit to our ability to compute cluster relationships. He has proposed a new algorithm that can efficiently extract clusters or communities of similar data from much larger, uncoordinated data sets. As the contest winner, Abbe will receive a cash prize of $100,000 and have the opportunity to pursue his work within Bell Labs over the next year.
Just as Bell Labs has helped shape major advances in the history of telecommunications, from national land line networks to powerful 3G and 4G data networks, Abbe’s work may play a key role in the advancement of the next great step forward in telecommunications.
Nearly 500 proposals from 31 countries were submitted to the inaugural contest hosted by Bell Labs, the research arm of Alcatel-Lucent and one of the world’s leading scientific research institutions.
In addition to his work at Princeton, Abbe received his Ph.D. from the Massachusetts Institute of Technology under the Shannon Fellowship and his M.Sc. degree from the Mathematics Department at the École Polytechnique Fédérale de Lausanne (EPFL).
We are proud to welcome Emmanuel Abbe to Bell Labs. Congratulations, Emmanuel!
–Marcus Weldon, President, Bell Labs