Yingxiang Yang and Jameson Toole, graduate students in Professor Marta González Human Mobility and Networks Laboratory (HuMNet), won first and second place, respectively, in the two categories of the MIT Big Data Challenge hosted by CSAIL and Transportation@MIT. The goal of the competition was to help the City of Boston better understand taxi ridership, such as the best locations for cab stands and specific locations and times of day that people most need taxis. The competition was two-pronged: predict the total number of taxi pickups at specific locations across Boston during a two-hour window based on historical taxi data and other related data sets, including weather, events and social media; and create the most compelling scientific visualization using this data. Yang and his team won first place in the prediction competition, and Toole won second place with his scientific visualization of one week’s taxi pickups and drop-offs. Yang’s team included graduate students Lauren Alexander, Serdar Colak, Suma Desu and Toole.