David Mobley is Professor in Pharmaceutical Sciences and Chemistry at UC Irvine where his work focuses on developing, testing, and applying computational tools to help guide pharmaceutical drug discovery including binding predictions of small-molecule ligands to proteins. He has a graduate degree in Physics from UC Davis and did his postdoctoral work with Ken Dill at UCSF working on free energy techniques based on molecular simulations. David is also one of the organizers of SAMPL (Statistical Assessment of the Modeling of Proteins and Ligands) which is a set of community-wide blind challenges aimed to advance computational techniques as standard predictive tools in rational drug design.