PhD, Applied Mathematics, University of Colorado, Boulder
Networks are widespread in technology, biology, and society. Moreover, they can encode similarity between arbitrary objects (i.e., images, videos, etc.) and thus play a crucial role for data-analysis methodology in general. I develop mathematical, statistical and machine learning tools to study network representations of complex systems and data. My work falls under two broad groups:
Importantly, these two groups are closely intertwined. That is, realistic modeling of dynamical systems typically requires assimilation with empirical data. At the same, data-analysis methodology often stems from the study of dynamics. Random walks, for example, are central to algorithms including PageRank, Infomap, and Diffusion Map. I study network dynamics and network data as a synergistic pursuit.