Jean Serra is, with George Matheron, the co-founder of the morphological approach to Image Analysis that has provided the basis for handling a vast range of problems in optical microscopy, histology, signal compression, multispectral imagery, material sciences and many other industrial settings. Most recently, he has turned his attention to environmental problems. Following his PhD studies at Nancy, he moved to the Paris School of Mines at Fontainebleau, where he subsequently established his own research group in Image Analysis and Mathematical Morphology. He has many writings and inventions to his name, including over 100 papers, 10 books, and several patents. He was founder and first President of the International Society for Mathematical Morphology. He has received numerous awards the ESCLANGON price, awarded by the French Society of Physics the first award of the Grand Prix of the AFCET Society (French equivalent of the IEEE), Chevalier of the National Order of Merit, France, and Doctor Honoris Causa of the Autonomous University of Barcelona.

In 2004, he wrote: "I am fascinated by the process that makes the world intelligible, and which, conversely, goes back from theory to an actual handling of things. That is the reason why I designed and patented image analysers, and why I launched several companies, for industrial control, for fingerprints, for quantitative microscopy, and others."

Lee Edlefsen is Vice President of Engineering of REvolution Computing, a venture-funded commercial open source company whose objective is to be to "R" what Red Hat has been to Linux. He holds a Ph.D. from Harvard University, and has had a long career developing data analysis and visualization software. He played a leading role in designing and developing three award-winning, commercially successful software programs (Gauss, Axum, and S-PLUS for Windows), and was the co-founder and CEO of three successful software companies.

Lee has had a long-standing interest in high performance computing and especially in the analysis and visualization of large complex data sets. Gauss, developed in the mid-1980's, was built on algorithms that allowed arbitrarily-large data sets, as, later, was Axum. Both won PC Magazine Editor's Choice awards. More recently, he served for several years as a consultant to organizations trying to deal with huge data challenges, and during that time developed ExaStat, an extremely fast interactive data analysis program capable of handling huge data sets and of distributing the computations across multiple computers and multiple cores on each computer. He is currently leading a project at REvolution Computing to add extremely fast, distributed, huge data capabilities to R.