My research spans security, privacy, and optimization of data collection particularly as applied to the Smart Grid, an augmented and enhanced paradigm for the conventional power grid. I am particularly interested in optimization approaches that take a notion of security and/or privacy into the modeling explicitly. At the intersection of the Intelligent Transportation Systems, Smart Grid, and Smart Cities, I am interested in data privacy and energy usage in smart parking lots. Protection of data and availability, especially under assault through a Denial-of-Service attacks, represents another dimension of my area of research interests. I am working on developing data privacy-aware bidding applications for the Smart Grid Demand Response systems without relying on trusted third parties. Finally, I am interested in educational and pedagogical research about teaching computer science, Smart Grid, cyber security, and data privacy.
I develop fast and principled methods for exploring and understanding one or more massive graphs. In addition to fast algorithmic methodologies, my research also contributes graph-theoretical ideas and models, and real-world applications in two main areas: (i) Single-graph exploration, which includes graph summarization and inference; (ii) Multiple-graph exploration, which includes summarization of time-evolving graphs, graph similarity and network alignment. My research is applied mainly to social, collaboration and web networks, as well as brain connectivity graphs.