Ivana is a Ph.D. student in the Biostatistics Division working with Mark van der Laan, Antoine Chambaz and Alan Hubbard. She earned her Master’s in Biostatistics and Bachelor’s in Mathematics, and spent a year working as a Freeport-McMoRan research fellow in Data Science and Bioinformatics at the Translational Genomics Research Institute (TGen). Some of her prior work centers around mathematical modeling and Bayesian models for allele specific expression.
Very broadly, her research interests span non/semi-parametric theory, probability theory, machine learning, causal inference and high-dimensional statistics. Most of her current work involves complex dependent settings (dependence through time and network) and adaptive sequential designs. She is also interested in model selection criteria, optimal individualized treatment, sensitivity analysis, mediation, online learning and software development (ex: medltmle, tstmle, tstmle01, sl3, cvma, tmle3opttx, tmle3cvim)
Ivana is also one of the founding members of the tlverse software ecosystem, and works as a biostatistician on multiple projects at the Kaiser Permanente Research Division, TGen and the Bill & Melinda Gates Foundation.