Publications

In cluster randomized experiments with selection bias due to recruitment, data are often only available on those that were recruited. …

We investigate the complications and opportunities when drawing causal inference from spatial observational data. We introduce causal …

Estimating the parameters of a temporal, spatio-temporal, or mutually-exciting Hawkes process based on data that are available in …

Basing estimation of tensor regression coefficients on a soft version of the PARAFAC approximation.

Extending causal inference in the presence of interference to bipartite settings where the interventional units are different from the …

We introduce a framework for estimating causal effects of binary and continuous treatments in high dimensions. The proposed framework …

Causal exposure-response curve estimation with local confonding adjustment. Different variables confound the exposure-response …

A review of the literature on the health effects of exposure to low levels of particulate matter.

Causal inference with interference for realistic treatment allocation programs. Evaluating the comparitive effectiveness of power plant …

Incorporating geographical distance in a propensity score matching approach to account for unmeasured confounding by spatial variables.