Samiul Hasan, a 2013 Ph.D. graduate from the Transportation and Infrastructure Systems area, was awarded the 2014 INFORMS Transportation Science and Logistics (TSL) Best Dissertation Award at the INFORMS annual meeting in San Francisco.

The TSL Dissertation award is the oldest and most prestigious honor for doctoral dissertations in the transportation science and logistics area. Past award winners have become successful researchers and leaders in the TSL community.

Hasan’s research developed novel data driven models ("big data") which reveal the behavior of the underlying phenomenon and improve system performance using large volumes of data from social media.  Hasan’s work is one of the first research work on developing new methodologies to understand urban mobility patterns to understand transportation network performance. This geo-location data offers us, in new ways, people's attitudes, interests and activity patterns over a wide network and over multiple months/years that was unimaginable before. However, while this new data is available, there are currently limited methodologies that allow the analysis of large data sets to obtain meaningful information by characterization of urban dynamics. Samiul’s dissertation presents a new paradigm for activity-travel behavior analysis by analyzing large-scale geo-location data, recording human movements over many days, to understand: i) long-term individual mobility patterns, ii) short-term individual activity patterns, iii) lifestyle choices and iv) to estimate network traffic congestion.

Hasan's dissertation makes fundamental contributions in  network science, optimization, simulation and data analytics. One important aspect of Hasan’s dissertation is not only the contribution to fundamental science but in the use of very large real-world data sets from New York City, particularly, the Foursquare and Twitter data from 29,000 individuals for over a year to estimate the activity models both at the individual and system level. In addition, the tools developed by Samiul are not specific to social media data but are applicable to other geo-location data such as cell phone data or GPS data from taxis.

The title of Hasan's dissertation is "Modeling Urban Mobility using Geo-location Data." His advisor is Professor Satish Ukkusuri.