Affiliation
Mathematical Consultant, MathSci.ai

Education
PhD, Applied Mathematics, University of Maryland, College Park
BS, Mathematics, University of Maryland Baltimore County

A native of Maryland (you might catch me saying “Warrrshington”), I earned a BS in mathematics from the University of Maryland Baltimore County and a PhD in applied mathematics from the University of Maryland College Park. Throughout my schooling and career, I worked at the intersection of mathematics, computing, and data. This was before data science was a science, at the dawn of the internet, in the pre-Google era.

After completing my doctorate, I was awarded the Alston S. Householder Postdoctoral Fellow in Scientific Computing at Oak Ridge National Labs in Tennessee. After that, I worked for more than two decades at Sandia National Labs in California, where I rose to the level of distinguished member of the technical staff. I’m a fellow of the Society for Industrial and Applied Mathematics and Association for Computing Machinery and a member of the National Academy of Engineering. I recently transitioned to independent research and consulting under the auspices of my company, MathSci.ai.

My research is in the broad area of mathematics of data science, and I expect I am best known for computational methods for tensor decompositions. These days, I am especially interested in randomized algorithms for massive data problems. I’ve also been exploring symmetric tensor representations of higher-order moments. My interest in data science has led me naturally to a deeper and deeper appreciation of statistics.

It was during my tenure at Sandia that I had the good fortune to work with a statistics graduate student named Eric Chi (now a professor at North Carolina State University). He showed up on my doorstep and asked to work with me, and I now credit him with starting me along the path whereby statistics has become integral to my work. I have continued to benefit from the advice and guidance of many other statisticians since then, and I find the community to be highly collegial.

A great achievement for me has been to help launch and serve as founding editor-in-chief of the SIAM Journal on Mathematics of Data Science, an academic journal focused on the mathematical and statistical foundations of data science methods. Our editors represent diverse fields such as including statistics, applied mathematics, mathematical signal processing, functional analysis, theoretical computer science, and numerical optimization. Great innovations are happening at the intersections of these fields, and I am privileged to witness it.