Networks are Everywhere

Intrinsic connectivity in the brain. Social networks of peer affiliation. Disease transmission. Gut protein interactions. Topic networks across social media. Algorithms that predict stock exchange patterns. What do these all have in common? Networks. I build and implement quantitative tools that estimate, model, and predict network structure, connectivity, and change over time.

I am currently a postdoctoral researcher in Cognitive Psychology and Neuroscience at the University of North Carolina-Chapel Hill, where I build network tools to assess functional connectivity across the brain. I received my PhD in Quantitative Psychology with a MSc in Statistics also from UNC-CH. Although I am currently focused on building network methods for functional and structural neuroimaging, I am also fascinated by the underlying similarities vs. unique challenges that network data pose across all different types of disciplines--from sociology and business to psychiatry and medicine.

My quantitative expertise is in mixture and agent-based modeling, Bayesian estimation, and exponential random graph models. My substantive expertise is in functional neuroimaging, adolescent development (e.g., autism, substance abuse), and natural language processing (e.g., political blog topic analysis).

 

Network Science & Statistics

Modeling complex dependencies using cutting edge statistical methods.

Functional Neuroimaging

Examining the brain on a functional connectivity level.

Natural Language Processing

 Networks of texts and texts of networks.