Brad Jones, JMP's Director of Statistical R&D, has been elected a Fellow of the American Statistical Association, the most prominent professional statistical society in the US. This honor recognizes "outstanding professional contributions to and leadership in the field of statistical science."
Brad has a career-long passion for the field of optimal experimental design. Experiments are the way you learn, by trial and error, how to make things work better, and optimal designed experiments are simply the way you learn the most from a given number of experimental trials. The world is too complicated to discover things by pure theory – we need some experimental data to find out how the world works.
For about 25 years, Brad has been working on a Big Idea that focuses most of his work. The Big Idea is that experimental design has to fit naturally within the workflow of an engineer, and the best way to make that happen is for great software to support that workflow. For new cutting-edge software to evolve, statisticians had to change the way they think about experimental design.
In the past, statisticians created designs by algebraic and geometric patterns; the resulting designs could accommodate only certain situations with fixed numbers of runs and factors. For example, if you had a budget for 17 runs on five categorical factors, you had to throw one run away to get a classical design. In the classical design world, there was a lot to learn, and that learning burden was an impediment to engineers.
Brad's Big Idea for the engineering workflow turned experimental design upside down. Instead of forcing conditions to fit a tabled design, you tell the computer software what your experiment is all about and how many runs you can afford, and the computer software creates a custom-built design for that situation – a design that is optimal for learning what you need to know from the experiment.
Brad adopted the field of optimal experimental design, and, with other statisticians in the field, pushed all the boundaries to make it a rich and robust field. One early breakthrough, by Chris Nachtsheim and Ruth Meyer, was a general algorithm to optimize the design, called coordinate exchange. Brad adopted and refined the coordinate exchange algorithm. Another significant development was Brad's work with co-author Bill DuMouchel on Bayesian D-Optimal designs. These designs try to estimate as many potential interaction effects as possible, even when they are not all estimable.
Then Brad recognized that the Bayesian D-Optimal method could be applied even to main effects, and he pioneered the optimal design for what are called supersaturated designs, which allow there to be more factors than runs. This occurs in screening situations where you expect only a few factors to be large, and the objective is to identify these large factors. In collaboration with Chris Gotwalt at SAS and other statisticians, Brad went on to pioneer I-Optimal designs, various space-filling designs, mixture designs, split plot designs, designs for nonlinear models, spherical designs, choice designs for market research and designs for computer experiments.
For the Big Idea to work – to get engineers used to designing experiments – there also had to be fitting and analysis tools. Here Brad invented a way to visualize a response surface by taking vertical cross sections across each factor, given fixed values of other factors. This tool, called the Profiler, is now implemented in just about every DOE fitting system. When Brad joined SAS to work with JMP, the Profiler was extended to provide complete optimization services and recently includes optimization in the presence of variability (stochastic optimization).
For the Big Idea to gain traction, Brad had to evangelize. To that end, he has established ties with many leading DOE researchers and has jointly authored papers with some of them. Brad is a regular speaker at academic statistics seminars, JMP seminars and academic meetings. One recent meeting was the International Conference on Design of Industrial Experiments at the University of Antwerp, where Brad presented the public defense of his PhD dissertation.
In the last two years, Brad has submitted numerous papers for publications, most of them with co-authors. For seminars, Brad and I developed a popular demonstration we call the "card trick" – which involves doing a live supersaturated screening experiment with the audience.
On the side, Brad is a concert violinist, a highly ranked Go player and author, has bred show dogs that compete nationally, and is a marathon runner. He was a published author in the field of photochemistry at age 17.
I am delighted to see Brad recognized as an ASA Fellow.
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