Latent Space Networks

Ranking methods for objects embedded in networks, such as journals in citation networks. Click the icon above for code accompanying a comment to "Statistical modelling of citation exchange between statistics journals" (JRSS-A, 2016). Click here for the comment and further work

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Bike Share

Development of time-dependent network models to identify the roles of stations in bike share systems. With a team from UCLA's applied math department, developed a multi-layer extension of degree-corrected stochastic blockmodels.

Exponential Random Networks

I contribute to the development of Ian Fellows' exponential random network models (ERNM) and accompanying R package, an expansion of exponential random graph models (ERGM). The model class allows for stochastic nodal covariates.

Respondent Driven Sampling

Respondent driven sampling is a network-based method for surveying hard-to-reach populations. I wrote front-end code in R+Java and documentation for RDS Analyst, software that enables public health professionals to perform respondent driven sampling.