Research Interest: study human behavior on the Web via an interdisciplinary approach of Computer and Psychological Sciences, for addressing the fundamental problem of information overload on a human mind. Specifically, I model individual behavior (e.g., intent, comprehension, and engagement) in offline and online social environments, to help reduce the information overload in supporting individual and group decision making. This research is employed in the design of systems for social good in future smart communities for a variety of domains, including natural crises (e.g., hurricanes), societal crises (e.g., migration, gender violence), and human crises (e.g., terrorism, cyber attacks).
My specific technical interest is to fuse top-down and bottom-up data mining approaches for developing explainable models by learning with prior knowledge (domain semantics and cognitive & social theories), which can help in both explaining and predicting individual and group behavior from unstructured social, open Web, and IoT data at scale.
Check more details and relevant projects of Humanitarian, Semantics & Informatics Lab (HSIL) research group.