Ivana Malenica

Bio/CV: 

Ivana is a Ph.D. student in the U.C. Berkeley Biostatistics Division, working with Alan Hubbard and Mark van der Laan. She earned her Master's in Biostatistics and Bachelor's in Mathematics, and spent some time at the Translational Genomics Research Institute. Some of her prior work includes mathematical modeling, Bayesian models for allele specific expression and time-series models for genomics data.
Broadly, her research interests span Machine Learning, Causal Inference, high-dimensional data, and semiparametric theory. Some of her current work has been centered around active learning, model selection criterion for dependent data, targeted estimators for parameters of semi and nonparametric models (recently, working with the natural mediation effect) and software development (medltmle, sl3).

Publications

Jeremy Coyle; Nima Hejazi; Ivana Malenica; Rachael Phillips; Alan Hubbard; Mark van der Laan
Book,