Mateo Diaz, assistant professor in the Department of Applied Mathematics and Statistics at the Whiting School of Engineering, has been named a recipient of the National Science Foundation’s (NSF) Early CAREER award, which recognizes early-stage scholars with high levels of promise and excellence.
Diaz’s project, “Scalable Optimization for Data Science: Complexity and Structure,” aims to advance optimization theory and algorithms to address modern data science challenges across sectors such as health care, energy, and finance. It focuses on understanding why certain simple heuristics, like stochastic gradient descent, perform remarkably well in nonconvex, nonsmooth settings, while traditional methods struggle to scale.
“The CAREER award will allow us to develop tools that analyze the computational and statistical complexity of widely used heuristics and, from these insights, design new algorithms that avoid common computational pitfalls,” said Diaz.