N’s for NA —but it’s not “Not Applicable”.
Its practical use is indeed undeniable.
What is NA, a new student asks.
We turn to Trefethen, who in the field basks.
Alg’rithms, he says, the study of which
Solve problems of math in th’ continuous niche.

Numerical analysis, as Nick Trefethen, our former colleague, will tell you, is the study of algorithms for problems of continuous mathematics —it is not just about rounding errors, accuracy, and approximation.

We are proud to have been a substantial player in the field of NA, or scientific computing as it is now called, right from the start. Jim Bunch (co-author of Linpack), Jorge More, John Dennis, Tom Coleman (now Dean at Waterloo), and Trefethen (now at Oxford University) all spent substantial time here.

The NA group is led by Charlie van Loan, whose coauthored book Matrix Computations is one of the most widely cited text in the computing and math sciences, and Steve Vavasis, whose automatic mesh generator is one of the most important software tools in solving boundary problems over irregular domains. Paul Chew’s work on mesh generation needs mentioning too.

The Cornell environment has helped NA flourish here, with strong ties to Math and the Center for Applied Mathematics. Interdisciplinary work is stronger than ever before. For example, there’s Uri Keich’s work on BLASTn for matches in DNA sequences, and Keshav Pingali’s advances in grid computing has contributed to the success of the work of Civil Engineer Tony Ingraffia and Vavasis on crack propagation in airplanes. And, as Van Loan will tell you, PageRank is an eigenvector computation!