Simon Mak


Assistant Professor of Statistical Science

Broadly speaking, I am interested in developing practical methodologies with theoretical guarantees for “big data” and “small data” analytics, both of which are important for solving real-world problems. Current research interests include the reduction of big and high-dimensional data, scalable Bayesian methods, computer experiments, and Monte Carlo and Quasi-Monte Carlo sampling. Much of my research is directly motivated from real-world engineering problems, fundamental scientific questions, and practical challenges in e-commerce. Current / past projects include the design of rocket engines for spaceflight (GT Aerospace), personalized surgery planning for aortic valve stenosis (Piedmont Hospital), and subsurface imaging for geothermal exploration (UGA).