Date/Time

Date(s) - 04/19/2018
4:30 pm - 5:20 pm

Dong Wang of the University of Notre Dame will speak at this Community Seminar.

Title: Assured information distillation in social sensing

Abstract: The proliferation of digital sensors and the advent of online social broadcast media (e.g., Twitter and Flickr) create a deluge of unfiltered, unstructured, and unvetted data about the physical environment. This opens up unprecedented challenges and opportunities in social sensing, where the goal is to distill reliable information from social sources and devices in their possession. This talk will present a new analytical framework and theories to obtain reliable information with quality guarantees from large amounts of unreliable social sensing data. Noticeably, our analytical framework is the first to jointly model the complex interactions among three deeply coupled networks underlying the data; namely, the information, social and physical networks. The talk will also introduce a new information distillation system we built, called Apollo, which has been applied in a wide range of social sensing applications. Examples include event/disaster tracking, smart road applications, environment monitoring, and anomaly detection. The talk will conclude with a few directions for future research.

A photo of Dong WangBio: Dong Wang is an assistant professor in Computer Science and Engineering Department at the University of Notre Dame. He received his Ph.D. in Computer Science from University of Illinois at Urbana Champaign (UIUC), an M.S. degree from Peking University and a B.Eng. from the University of Electronic Science and Technology of China, respectively. His research interests lie in the area of social sensing, big data analytics, cyber-physical-human systems, and smart city applications. Dong Wang has published over 70 technical papers in conferences and journals. His research on social sensing and CPS resulted in software tools that found applications in academia, industry, and government research labs. He recently authored a monograph “Social Sensing: Building Reliable Systems on Unreliable Data” published by Elsevier 2015. He received the Google Faculty Research Award in 2018, Young Investigator Program (YIP) Award from Army Research Office in 2017, Wing Kai Cheng Fellowship from University of Illinois in 2012 and the Best Paper Award of IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS) in 2010.  Dr. Wang’s website: http://www3.nd.edu/~dwang5/