Computational Intelligence - November 2012 - 6

formal platforms of information granularity. Another idea introduced by
him, an optimal allocation of information
granularity, is a useful concept unique
to Granular Computing, which
becomes instrumental in designing
models that are in better affinity with
real-world systems.
Pedrycz's accomplishments were
recognized by prominent awards and
recognitions awarded to him by peer
professionals; among others these
include a prestigious Norbert Wiener
award (the highest award from IEEE
Systems, Man, and Cybernetics Society), K.S. Fu (the highest honor
bestowed by the North Amer ican
Fuzzy Information Processing Society), and foreign membership of the
Polish Academy of Sciences. The visibility of his contributions is reflected
in the citation record of his scholarly
work. He is on the list of Highly
Cited Researcher s-Highly cited
researcher on ISI HighlyCited.com. He
is Fellow of the IEEE and IFSA
(international Fuzzy System Association). He has been serving as President
of NAFIPS and IFSA. Since 2001
WitoldPedrycz is Canada Research
Chair. He was conferred the title of
National Professor by the President of
Poland. He held positions of Visiting
Professor of the Nottingham Trent
University, Nottingham, UK, and
Distinguished Visiting Scholar in the
University of Technology Sydney, Australia. He is also a speaker in the IEEE
Distinguished Lecturer Program and a
Senior Fellow of the Japan Society for
Promotion of Science (JSPS). In 2009
he has received a highly prestigious
Cajastur Prize for Soft Computing
from the European Centre for Soft
Computing for "pioneering and multifaceted contributions to Granular Computing." He is listed in Who is Who,
Canadian edition, since 2003. He
serves as Editor in Chief of three
highly influential and acclaimed
research archival publications: IEEE
Transactions on Systems, Man, and
Cybernetics-Part A (a flagship publication of the IEEE Systems, Man, and
Cybernetics Society), Infor mation

Sciences (Elsevier) and Wiley Interdisciplinary Reviews on Data Mining
and Knowledge Discover y
(J. Wiley). Just recently, in July 2012 he
was elected a Fellow of the Royal
Society of Canada (RSC).
Evolutionary Computation
Pioneer Award
Xin Yao, University of Birmingham, UK
For contributions to theory and applications
of evolutionary computation.
Xin Yao obtained
h i s b a c h e l o r 's
degree from the
University of Science and Technology of China
(USTC) in Hefei
in 1982, master's degree from the
North China Institute of Computing
Technology (NCI) in Beijing in 1985,
and doctorate's degree from USTC in
1990, all in computer science. His
Ph.D. thesis on simulated annealing
won the President's Award of the Chinese Academy of Sciences for Outstanding Thesis in November 1989,
which was competed nationally.
Dreaming of soaking up sunshine
under a blue sky, he took up a postdoctoral fellowship in the Computer
Sciences Laboratory (CSL), Research
School of Physical Sciences and Engineering at the Australian National
University in 1990, not long after his
Ph.D. defence. (The Computer Sciences Laborator y is now in the
Research School of Information Sciences and Engineering.) He continued
his research in stochastic search algorithms. In February 1991, he published
his first hybrid evolutionary and simulated annealing algorithm (X. Yao,
"Optimization by genetic annealing,"
Proc. of the 2nd Australian Conf. on
Neural Networks (ACNN'91), ed. M.
Jabri, Sydney, pp. 94-97, 1991), which
embedded a fast simulated annealing
procedure as local search into evolutionary algorithms. Before evaluating
an individual's fitness, a simulated
annealing procedure was applied. This

IEEE ComputatIonal IntEllIgEnCE magazInE | novEmbEr 2012

hybrid algorithm can be regarded as
one of the earliest memetic algorithms
although the term was not used at that
time. The term of genetic annealing
has not been used much since then,
partly because one of the conference
attendees commented that it gave him
the mental imagine of people suffering
in fires!
Being sur rounded by leading
researchers in artificial neural networks at CSL, yet unwilling to give
up his passion for evolutionary computation, he started working on the
evolutionar y of neural networks,
which he presented at a symposium
held at the Lamington National Park
near Brisbane, Australia (X. Yao, "Evolution of connectionist networks,"
Preprints of the Symp. on AI, Reasoning, and Creativity, ed. T. Dartnall,
Brisbane, pp. 49-52, 1991. Later published as X. Yao, "The evolution of
connectionist networks," In Artificial
Intelligence and Creativity: An Interdisciplinary Approach, ed. T. Dartnall,
Kluwer Academic Publishers, Dordrecht, pp. 233- 243, 1994). He formulated systematically three levels of
evolution in artificial neural networks
and a general framework of adaptive
systems based on them. The explicit
identification of the evolution of
connection weights, architectures and
learning rules has laid a solid foundation for the further development of
evolutionary artificial neural networks
a n d f o l l owe d by m a ny o t h e r s .
Between 1991 and 1996, he published
14 papers on evolving neural networks. He has continued his research
in this area since, the latest topic
being the evolution of neural network ensembles.
Equipped with all the sunshine he
soaked up in Canberra, he moved
to Melbourne in August 1991 as a
post-doctoral research fellow in the
Knowledge-Based Systems Group,
CSIRO (Commonwealth Scientific
and Industrial Research Organization)
Division of Building, Construction and
Engineering, working on an industrial
project on automated sewage pipe
inspection, applying his experiences

http://www.HighlyCited.com

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