Alex is a Postdoctoral Researcher at the Predictive Science Lab, where he also earned his PhD. His research focuses on the theory of Bayesian inverse problems primarily through the lens of information field theory. He has also worked on applications in combustion engines, biomedical imaging, and thermal protection systems. At Purdue, he teaches ME 539 and 697. Before joining the PSL, he earned an MS in Applied Mathematics at the University of Akron under the supervision of J. Patrick Wilber and D. Dane Quinn.