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Department of Computer Science Seminar
2014 Series

Location Based Social Network for Disease Surveillance

Dr. Zhuojie Huang
Center for Infectious Disease Dynamics
Penn State University

Date: January 7, 2014 (Tuesday)
Time: 10:30 - 11:30 am
Venue: SCT716, Cha Chi Ming Science Tower, Ho Sin Hang Campus

Enormous amounts of digital traces left by individuals by the usage of mobile devices are created every day. Most of these digital traces, such as geo-tagged tweets and cellphone data records, are embedded with different levels of granularity of health and geographical information. These spatial-referenced trajectories form the basis of location-based social networks, linking people's health behavior and location characteristics together. Here, we review approaches in GIScience and big data analytic to summarize the four dynamics between people and location on various forms of location-based social networks. Coupled with the big data deluge from the public health surveillance, epidemic intelligence, demographic information, environmental risk exposures and disease mapping, the spatial-temporal analysis on the interactions of people and locations can provide valuable local and timely information about disease and health dynamics in populations around the world.

Dr Zhuojie Huang is Cantonese, born in Guangzhou, China. He obtained his undergraduate degree in Land Resources Management from the South China Agricultural University in 2007, Master of Science in Geography and PhD in Medical Geography from the University of Florida in 2009 and 2013. His current position is Postdoctoral Data Scientist at the Center for Infectious Diseases Dynamics, Penn State University. He has developed a unique research niche, applying and developing big data analytic, GIScience and quantitative techniques for evidence-based public health strategies. His recent works are focused on analyzing cell phone data, fine scale GPS data, geo-tagged tweets and air travel network for the dispersal of infectious diseases in relation to population movements for public health planning and decision supports. His contact info can be found at

********* ALL INTERESTED ARE WELCOME ***********
(For enquiry, please contact Computer Science Department at 3411 2385)
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