\documentstyle[12pt]{article}

\pagestyle{empty}

\begin{document}

\centerline{\bf RESEARCH SUMMARY}
\bigskip

Dr Coddington has been working in the area of computational science
and parallel computing for more than 8 years, almost from the beginnings
of applied parallel computation in the early 80's. He obtained a Bachelor
of Science degree with first class honors from the University of Western
Australia in 1982, and his Ph.D. in 1988 from Southampton University, 
one of the leading universities in England for research in parallel
computing. He is a member of the American Physical Society.

Dr Coddington's original research includes contributions to both theoretical 
and computational physics, in particular the development of new algorithms 
for parallel computers.
His research on lattice gauge theory and the quantum Hall effect was among
the earliest work in these fields to use high performance parallel computers.
His work on new techniques for gauge fixing in lattice gauge theory has been
cited in many recent publications, as interest in this method has increased 
greatly in the last few years.
He has contributed to the study of solid state physics, spin models, 
gauge theories, and quantum gravity, and especially the computer simulation 
of these problems. He pioneered the development of parallel algorithms for 
some of these problems, especially cluster Monte Carlo methods.
Use of these algorithms on parallel supercomputers has enabled accurate 
measurements of the dynamic critical exponents of cluster Monte Carlo
algorithms to be performed, which is important for understanding the 
mechanism by which these new algorithms work.
The same parallel algorithms can also be used for connected component
labeling, which is an important part of image processing and computer vision.
These algorithms are archetypal irregular problems which also provide 
important benchmark tests for parallel hardware, software and languages. 

Dr Coddington is considered an expert in parallel algorithms for computational
science, particularly in the field of Monte Carlo simulation.
He has also worked on parallel algorithms for solving matrix problems and
partial differential equations, in particular porting existing sequential 
programs to parallel computers.
He has experience in using a wide variety of parallel computers, including
the DAP, Meiko Computing Surface, nCUBE/10 and nCUBE/2, Symult 2010, 
Encore Multimax, Sequent Symmetry, BBN Butterfly, Intel Delta,
CM-2, CM-5, MasPar, and workstation networks; and almost as many parallel
languages, including Occam, DAP Fortran, CM Fortran, MasPar Fortran, *Lisp,
C*, MPL, and Express C and Fortran.

Dr Coddington has had 9 papers published in leading international journals in 
both physics (Physical Review B, Physical Review Letters, Nuclear Physics B,
Physics Letters B, Journal of Physics C, Europhysics Letters)
and computational science (Concurrency: Practice and Experience,
International Journal of Modern Physics C), and had 10 papers published in
the proceedings of international conferences on computational science.

Dr Coddington has been asked to review the work of others in similar
academic fields, by refereeing papers of other authors for international
journals (Physical Review, International Journal of Modern Physics) 
and conferences (The International Symposium on High Performance 
Distributed Computing).

Dr Coddington's work has been cited by other researchers in 11 publications 
in international journals prior to this year.
His more recent research on parallel algorithms for cluster Monte Carlo 
methods is pioneering work in this field, and
has been cited in at least 3 recent unpublished papers, 
and in one case formed the basis for that research.

Dr Coddington is currently employed as a Research Scientist at the 
Northeast Parallel Architectures Center (NPAC) at Syracuse University. 
He is leading a project to study the use of high performance parallel
computing in the power utility industry, 
to develop new parallel algorithms for the simulation of power networks, 
and to port existing sequential programs to parallel computers.
This includes the development and implementation of parallel algorithms 
for sparse matrix computations and differential-algebraic equation solvers,
which are also applicable to a number of other industrial applications.
This work is expected to greatly improve the accuracy of computer
simulations of power grids, and to consequently improve the reliability
and efficiency of electrical power generation and distribution.
%
This project is part of ACTION, NPAC's industrial outreach program.
Dr Coddington has had previous experience working with 
the Transputer Support Center, a similar program associated with
Southampton University, which provides a consultancy and teaching 
facility aimed at increasing the use of parallel computing by industry. 

\end{document}


