Bruce Hendrickson
Sandia National Laboratories
Although scientific computing is generally viewed as the province of differential
equations and numerical analysis, combinatorial techniques have long played
a crucial role. For example, graph theory is essential to the study of molecular
structures and material science. Many problems in linear algebra involve
discrete algorithms. And the parallelization of scientific computations
leads to numerous combinatorial problems. I will review some of these many
successes, and offer suggestions for new areas in which work is needed at
this exciting intersection of disciplines.