Meet Dr. Warren Pettine

Advisor: Dr. John D Murray

Institution: Yale School of Medicine

Bio:  Dr. Warren Woodrich Pettine (he, him) is a postdoctoral fellow with Dr. John D Murray at Yale University. During medical school in Colorado, Dr. Pettine studied attention circuits as Howard Hughes Medical Fellow with Dr. Tirin Moore at Stanford. He was then a postdoctoral associate in the theoretical neuroscience lab of Dr. Xiao-Jing Wang at NYU, where he received training in computational methods. Dr. Pettine's approach centers on developing computational models and experimental tasks to investigate judgements under uncertainty and decision confidence. To do this, he utilizes biophysical neural networks, algorithmic reinforcement learning, Bayesian inference, machine learning and online tasks. Dr. Pettine is particularly interested in how this research can improve decision-making in the real world.

Abstract:  Both the world and our assessments of the world are full of uncertainty. Yet, people often struggle to think of outcomes in probabilistic terms. Moreover, there is often a disconnect between the confidence in one’s judgment and how certain one is if an event will occur. These issues are particularly acute for intelligence analysts tasked with assessing the likelihood of events. The uncertainty they assign to an event could be due to the quality of information they are drawing from, their assessment of their own knowledge of the topic, or even the degree of randomness in an outcome. All these forms of uncertainty have been studied extensively by decision neuroscientists. In this project, we aim to apply findings from decision neuroscience to develop a training tool that improves assessment of uncertainty.