CS450 alumnus, class of 2010, Can Kilicbay has just started his own kick ass tumblr blog! Welcome to the club Can!
Within the Sabin+Jones LabStudio, architects, mathematicians, materials scientists and cell biologists are actively collaborating to develop, analyze and abstract dynamic, biological systems through the generation and design of new tools. These new approaches for modeling complexity and visualizing large datasets are subsequently applied to both architectural and biomedical research and design.
“Yekpare” is a storyteller which narrates the 8500 year story of Istanbul. The story embraces symbols from Pagans to Roman Empire, from Byzantine Empire to Latin Empire, and finally from Ottoman Empire to Istanbul at the present day.
Haydarpaşa Train Station, with its brilliant architectural forms, is the building on which the story is projected. The connection between middle east to west has been provided by Istanbul and Haydarpaşa since 1906. In the 50’s it served as a door for millions of internal emigrants who have triggered the chaos in Istanbul’s dialectical daily life scenes.The project’s conceptual, political and geographical positioning, the location’s depth of field and the fact that the entire show can be watched from Kadıköy coast; make “Yekpare” a dramatic presentation.
More info: http://www.vimeo.com/12584289
From the abstract:
Vacation planning is one of the frequent—but nonetheless laborious—tasks that people engage themselves with online; requiring skilled interaction with a multitude of resources. This paper constructs intra-city travel itineraries automatically by tapping a latent source reflecting geo-temporal breadcrumbs left by millions of tourists. For example, the popular rich media sharing site, Flickr, allows photos to be stamped by the time of when they were taken and be mapped to Points Of Interests (POIs) by geographical (i.e. latitudelongitude) and semantic (e.g., tags) metadata.
Leveraging this information, we construct itineraries following a two-step approach. Given a city, we first extract photo streams of individual users. Each photo stream provides estimates on where the user was, how long he stayed at each place, and what was the transit time between places. In the second step, we aggregate all user photo streams into a POI graph. Itineraries are then automatically constructed from the graph based on the popularity of the POIs and subject to the user’s time and destination constraints.