Babak Shahbaba is Assistant Professor at the University of California, Irvine. His research focuses on developing Bayesian methods and applying them to real-world problems. He is currently conducting research in three areas: (1) incorporating appropriate priors into statistical models in order to improve their performance, (2) developing new nonlinear models that are sufficiently flexible and provide interpretable results, and (3) applying novel statistical methods to solve research questions in genetics, genomics, proteomics, and cancer studies.