Research Interest: Investigate individual and collective behavior dynamics in online spaces to design intelligent/AI systems with safeguards for real-time data analytics and information management at public sector and nonprofit workplaces that augment analytical abilities while ensuring human control of algorithmic behavior. I create human-centered computing methods that facilitate effective human-AI collaboration to observe, model, and analyze behavior in online social networks at scale, using new semantic computing, NLP, and ML techniques guided by socio-psychological theories. This research is employed in the design of information systems for social good applications and future smart city services for a variety of domains, including natural crises (e.g. hurricanes), societal crises (e.g. hate, gender violence), and human crises (e.g. terrorism, cyber attacks).
Technical Interest: Fuse top-down and bottom-up data mining approaches to develop explainable computational models with domain knowledge and cognitive/social theories, which helps in both predicting and explaining implicit behavior in unstructured social, web, and IoT data streams at scale.
Relevant projects:
Check Humanitarian Informatics Lab (Human_Info_Lab) research group page.
Grants and Acknowledgement:
We are grateful to the following agencies for supporting our research and its integration into education: U.S. National Science Foundation (NSF), Commonwealth Cyber Initiative (CCI), Virginia; Oak Ridge Institute for Science and Education (ORISE), U.S. Office of Navel Research (ONR), U.S. Department of Homeland Security (DHS), 4VA Program and CAHMP Center at Mason, as well as Western Norway Research Institute with Research Council of Norway (RCN):
Selected Publications: (full list: Google Scholar Profile)
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