Research Interest: investigate human behavior in online data streams via interdisciplinary research in Information and Psychological Sciences that informs the design of intelligent/AI systems to augment human capabilities at workplaces, especially realtime information and knowledge management. I create human-centered computing methods using human-AI collaboration to observe, model, and analyze individual/group behavior (e.g., intentional) in online social environments at scale, with 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 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 streams at scale.
Relevant projects: check Humanitarian, Semantics & Informatics Lab (Human_Info_Lab) research group page.
Acknowledgement. We are grateful to U.S. National Science Foundation (NSF), Office of Navel Research (ONR), and Research Council of Norway for supporting our research. Check grants at the Human_Info_Lab page.