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.
My current research focus is on modeling and simulating the value and benefits of various data sharing and policy trade offs. Typically these utilize system dynamics methodologies and tools.
I also have considerable experience across multiple industries with developing processes to enable industry and faculty to identify and solve data science problems using SAS tools.