Department of Computer Science and Engineering
Interdisciplinary Center for Network Science and Applications (iCeNSA)
University of Notre Dame
Email: dwang5 at nd dot edu
The advent of online social media (e.g., Twitter and Flickr), the ubiquity of wireless communication capabilities (e.g., 4G/5G and WiFi), and the proliferation of a wide variety of sensors in the possession of common individuals (e.g., smartphones) allow humans to create a deluge of unfiltered, unstructured, and unvetted data about their physical environment. This opens up unprecedented challenges and opportunities in the field of social sensing, where the goal is to distill accurate and credible information from social sources (e.g., humans) and devices in their possession that accurately describes the state of the physical world. The problem requires multi-disciplinary solutions that combine data mining, statistics, network science and cyber physical computing. My research addresses the aforementioned needs by building theories, techniques and tools for accurately extracting high quality information from data generated with humans in the loop, and for reconstructing the correct "state of the world" both physical and social. I believe my research can lead to the next generation of information distillation services, where predictable, reliable, and timely answers are found from the huge amount of real-time and heterogeneous data feeds, empowering humans to better understand, utilize and make sound decisions from such data.