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My main research interest lies in developing machine learning and large-scale data mining methods for the analysis and modeling of large real-world networks and processes that take place over them. In this context, there is a wealth of research problems and high-impact applications in social networks, information systems, marketing, epidemiology, business intelligence, and national security. For example, identifying influential users in social networks can become a multi billion dollar industry; detecting the spread of rumors and misinformation can improve information reliability and trustworthiness; designing user interfaces that mitigate information overload can increase users ’ engagement and improve workers ’ productivity; early detection and control of disease spreads can save lives. My research consists of several dimensions: (1) developing realistic models of networks and processes that take place over them, assessing their theoretical properties and limitations; (2) developing machine learning algorithms to fit such models and computational methods to influence processes over networks; (3) validating these models and methods in massive real-world datasets of gigabyte and terabyte scale. In the upcoming years, I would like to focus on building models and algorithmic inference method