The use of computational, mathematical, and statistical modeling in various areas of science has grown dramatically in recent years, triggered by massive increases in computing power and data acquisition. Mechanistic models for physical problems that reflect underlying physical laws are now being combined with data-driven approaches in which statistical inference and optimization play key roles. These developments are transforming research agendas in statistics, computer science, and applied mathematics, and are impacting a broad range of scientific disciplines.
In response to the critical need to train a new generation of computational and applied mathematicians who can confront data-centric problems in the natural and social sciences, the University of Chicago created the Committee on Computational and Applied Mathematics (CCAM) in 2016. The committee is an interdisciplinary program that provides graduate training in Computational and Applied Mathematics (CAM). It reflects both the new scientific demands and the unique strengths of the University of Chicago faculty across the Division of the Physical Sciences.
The first CAM PhD students arrived in Fall 2017, and the first cohort of MS students arrived in Fall 2019. . These graduate programs followed the creation of a successful interdisciplinary undergraduate major in CAM at the University. It was also enhanced by a faculty hiring initiative in computational and applied mathematics (CAMI) within the statistics department.