I’m RM Causey, and I’m a visiting assistant professor at Miami University. My interests are probability, statistics, financial math, actuarial science, signal processing, compressed sensing, greedy algorithms, and computer implementation of any of these notions. In particular, I enjoy working among the many real-world confluences of the areas of probability, statistics, analysis, linear algebra, convex geometry, and functional analysis.

I earned a Ph.D. in mathematics from Texas A&M University in 2014. I passed the P and FM actuarial exams in the spring of 2017, and I am currently working toward an M.S. in statistics at Miami University. I was employed as a Postdoctoral Fellow at the University of South Carolina from 2014 and 2016. Since then, I have been employed as a Visiting Assistant Professor at Miami University, where I teach, conduct scholarly research, and lead student research.

My Ph.D. research had a dual focus in infinite-dimensional Banach space theory and high dimensional probability with applications to convex geometry. It was there that I learned of the beautiful intersection of linear algebra, geometric functional analysis, and probability. These topics are used to prove powerful results about random vectors and random matrices, such as the Johnson-Lindenstrauss Lemma and the existence of RIP matrices used for sparse recovery in Compressed Sensing. In recent years, my interest has turned to topics of a more applied nature, such as stochastic processes with applications to finance, principal component analysis, Monte Carlo simulation, and generalized linear models, as well as the programming skills required to implement such methods.