Eaman Jahani

TL;DR: Manimal as discussed by the authors automatically analyzes MapReduce programs and applies appropriate data-aware optimizations, thereby requiring no additional help at all from the programmer, and it successfully detects optimization opportunities across a range of data operations.

TL;DR: Manimal is shown, which automatically analyzes MapReduce programs and applies appropriate data-aware optimizations, thereby requiring no additional help at all from the programmer, and that it yields speedups of up to 1,121% on previously-written Map Reduce programs.

TL;DR: Practical limits to the predictability of life outcomes in some settings are suggested and the value of mass collaborations in the social sciences is illustrated.

TL;DR: A framework to extract more than 1400 features from standard mobile phone data and used them to predict useful individual characteristics and group estimates is developed and validated by showing how it can be used to reliably predict gender and other information for more than half a million people in two countries.

TL;DR: This study analyzes segregation in economic and social interactions by observing credit card transactions and Twitter mentions among thousands of individuals in three culturally different metropolitan areas to show that segregated interaction is amplified relative to the expected effects of geographic segregation in terms of both purchase activity and online communication.