Simon Mak

About me

I am an Assistant Professor in the Department of Statistical Science at Duke University. 

I work broadly on developing novel ML / AI methods, theory and algorithms for advancing science and engineering. Much of my current research is on interpretable statistical models that integrate and/or learn scientific principles (e.g., mechanistic equations), as well as methods that leverage such models to guide efficient scientific decision-making. My research is motivated by and applied to ongoing interdisciplinary collaborations in high-energy and nuclear physics, aerospace engineering, bioengineering and public policy. I am currently an Associate Editor for Technometrics and Data Science in Science, and my awards include the ISBA Blackwell-Rosenbluth Award, the ISEA Young Statistical Engineer Award, the ASA SPES Award, and best paper awards from the ASA, INFORMS and IISE.