Seeking PhD students and postdocs interested in an elegant combination
of functional programming and big-iron style numeric computing.
Functional Programming and Automatic Differentiation
We are adding exact first-class derivative calculation operators
(Automatic Differentiation or AD) to the lambda calculus, and
embodying the combination in a production-quality optimising compiler.
Our research prototype compiler generates object code competitive with
the fastest current systems, which are based on FORTRAN. We are
seeking PhD students and postdocs with interest and experience in
relevant areas, such as programming language theory, numeric
computing, machine learning, numeric linear algebra, differential
geometry; and a burning drive to help lift big iron numeric computing
out of the 1960s and into a newer higher order. Specific sub-projects
include: compiler and numeric programming environment construction;
writing, simplifying, and generalising numeric and machine learning
algorithms through the use of type theory and AD operators; and
associated type/lambda calculus/PLT/real computation issues.
Project headquarters: Hamilton Institute, NUI Maynooth, Ireland,
Applications and queries to:
“Barak A. Pearlmutter” <firstname.lastname@example.org>