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Fábio Duarte Principal Research Scientist, MIT Senseable City Lab Nikita Klimenko Research Fellow, MIT Senseable City Lab
Assistant
Principal Investigator Susumu Tonegawa
In recent years, great strides have been made to scale and automate Big Data collection, storage, and processing, but deriving real insight through relational and semantic data analysis still requires time-consuming guesswork and human intuition. Now, novel approaches designed across domains (education, medicine, energy, and others) have helped identify foundational issues in general data analysis, providing the basis for developing a “Data Science Machine,” an automated system for generating predictive models from raw data.
2016 MIT Information and Communication Technologies Conference