Updated
4 December 2008
Professor David S. Brée
Institute
for Scientific Interchange,
Torino, Italy
Emeritus Professor of Artificial Intelligence
School of Computer Science, University of Manchester, UK
email: bree AT cs.man.ac.uk
David
S. Brée is currently Senior Researcher at the Institute
for Scientific Interchange, Turin, Italy. He is also Emeritus Professor of
Artificial Intelligence at the School of Computer Science at Manchester
University, UK.
- He has an MA in Mechanical Sciences from the Department of Engineering, Cambridge
University.
- His PhD, under Prof. Herbert
.A. Simon from Carnegie-Mellon
University, USA, was on styles for understanding the solutions to
problems.
- He was a Senior Lecturer at the Manchester
Business School (1968-70), where he set up their PhD Programme.
- Then he spend 20 years in the Netherlands as the Professor of
Psychology at the Rotterdam School of
Management (1970-1990). During this time he was the author of two
national reports: on PhD education in Management for the Netherlands
(1972) and on Artificial Intelligence in the Netherlands (1983).
- He was the first Scientific Director of the Dutch Stichting for
Knowledge-Based Systems, which he set up in 1987, with an injection of
€4,500,000 from the Dutch government for which he secured matching
funding.
- He joined the School of Computer Science at Manchester as
Professor of Artificial Intelligence in 1990.
He publishes on modelling of financial markets and the
semantics of natural language. His present projects include models of financial
crashes and the construction and enumeration of magic squares.
Research interests
- Financial markets: Financial
markets play an important role in our lives, in particular when they
crash. Being able to predict or understand the causes of such crashes is
an interesting topic. I have recently had two PhD students in this
area. One, Rob Woolfson, has built a workbench for testing the claims of
practitioners who propose a strategy for price prediction - no strategy so
far tested is able to outperform the market in modern times. The other, Gilles Daniel, built an
agent-based model of an open book double auction financial market.
He is able to reproduce most of the stylised facts of such markets, e.g.
the distribution of order arrivals, transactions and prices changes. I am
currently testing a well-known model of price fluctuations preceding
crashes, to see whether or not it holds up across different markets and
different periods.
- D. S. Brée and N. Joseph, Log Periodic Power Law fits to
financial crashes: a preliminary replication, Econophysics Colloquium
and beyond. Ancona, 27-29 September 2007.
- Magic squares: their
construction and enumeration. The construction of magic squares has
fascinated laymen and mathematicians alike for centuries. However there
still does not exist a method for constructing all of these squares. A
method for constructing a sub set of magic squares, called most-perfect
squares, originally developed by Dame Kathleen Ollerenshaw, was
refined by the two of us. We can also enumerate them, for any n. I have recently developed a method for constructing and
enumerating all regular pandiagonal squares.
- Semantics of time The way we
express temporal relations in natural language varies considerably between
languages. Tense and aspect have been much studied by linguists. I am particularly
interested in a third method: prepositions and conjunctions. By analysing
grammars of various languages it is possible to get a superficial account
of the use of these temporal prepositions. However, this is never complete
nor accurate. With the advent of text corpora it has been possible to
study the way prepositions are actually used to indicate temporal
relations. I have developed a framework for analysing such use in English.
It has also been applied to Dutch and German, and, to a limited degree, to
Chinese and Japanese. I am completing an analysis of the use of
temporal prepositions in the old Brown corpus of American English.
- Event recognition People have a
wonderful ability to recognise an event from a sequence of sounds, e.g. a
bird's song, a musical tune or a telephone bell, even after only a few occasions.
I have been interested in developing a system that will learn to recongise
a temporal event from a sequence of sub events. In particular, given some
model of what to expect, to adjust the temporal parameters in the model so
that temporal events can be reliably distinguished. Together with my
student Dr. George
Paliouras, we created a system for recognising the song of the hump
back whale from a very limited number of recordings.
My CV.