My research interest is in "computational social science", a newly emerging area that lies at the intersection of machine learning, social science, and human computer interaction. Specifically, I am interested in understanding human behavior from online footprints, utilizing/developing computational methods and leveraging big data.
The widespread proliferation of different social websites, including Facebook and Twitter has opened up a new vista of opportunities to researchers to study micro and macro-scale social processes, an important aspect of it being deciphering individual and collective behavior. Almost inconceivable scarcely a decade ago, study of these social phenomena, carries the potential to impact our lives in a significant way. Important domains that bear the likelihood to benefit from the study of social processes include: healthcare, economics and economic decision-making, urban planning, distributed social search of information as well as promoting effective collaboration in organizations.
My key insight is that human behavior is manifested in three key aspects—activity, interaction with others, emotion and language. In these lines, my research agenda has investigated how observed social activity, interactions, emotion and linguistic expression online can together be harnessed to understand individual level and collective behavior. My vision is to develop efficient and scalable models and algorithms, as well as conduct empirical and experimental studies to make a difference to important real-world societal problems, such as ones spanning healthcare, in order to improve the quality of life of people in general.
For more information, please refer to my research statement.