Bruno Di Stefano, P.Eng. (@ Nuptek Systems Ltd)
2006-04-10 04:32:44 UTC
Title
=====
"Feature Extraction in Computational Intelligence"
An IEEE Computational Intelligence Society Distinguished Lecture
Speaker
=======
Professor Evangelia Micheli-Tzanakou
Department of Biomedical Engineering
Rutgers University
Piscataway, NJ, U.S.A
Day and Time
============
Monday, April 10, 2006
6:30 - 8:00 pm (refreshments will be served at 6:00 p.m.)
Location
========
Hart House, Debates Room (2nd floor front)
7 Hart House Circle
University of Toronto
Toronto, ON M5S 3H3 map - code HH
Organizer
The Signals & Computational Intelligence Joint Chapter
Contact
=======
Bruno Di Stefano
Abstract
========
One of the major problems a researcher faces is what is learned from
data obtained by various methods and different techniques. This tutorial
will discuss and compare topics such as: Statistical Advances and
Challenges, as well as Feature Extraction in Computational Intelligence
methodologies.
Often a simple model describes the data well, simply because the S/N
ratio is too small for detection of more complex structures-which for
example is the case with medical data involving human subjects. One has
a lot of variability both in intra- and inter-sets of data.
Some important Simple Tools that have been used for a long time are:
Linear Regression, Discriminant analysis, Principal Component Analysis etc.
In all of these, the size of the data set matters. Huge data sets create
memory problems. The question is how do we handle different data types
and how do we handle them? What if the data are correlated? What if we
have complex data structures?
In this lecture you will learn more about Computational Intelligence,
how to get to know your data and how to do Feature Extraction. Some
examples of "features" will be given and different feature extraction
methods will be discussed.
Biography
=========
Evangelia Micheli-Tzanakou is Professor II and Director of the
Computational Intelligence Laboratories ( www.cil.rutgers.edu) in the
Department of Biomedical Engineering at Rutgers and an adjunct professor
of the University of Medicine and Dentistry of New Jersey. Dr Tzanakou
was Chair of the BME Department for 10 years and established the
Undergraduate curriculum in the same. She is a Founding Fellow of AIMBE,
a Fellow of IEEE and a Fellow of the New Jersey Academy of Medicine. She
has published two books: "Supervised and Unsupervised Pattern
Recognition: Feature Extraction and Computational Intelligence" was
published by CRC Press in January 2000 and co-authored a book with S.
Deutsch on "Neuroelectric Systems", published by New York University
Press, in 1987. She has published over 250 scientific papers in
journals, conference proceedings and book chapters. She has also edited
several books and conference proceedings.
Dr. Tzanakou has established the first ever experimental Brain to
Computer Interface (BCI), using the ALOPEX algorithm, in 1974. This
method is now used for target optimization in Parkinson's disease.
ALOPEX has also been used in a wide variety of problems: signal
processing, image processing, pattern recognition, transportation and
many more.
Dr. Tzanakou is Book Series Editor in Biomedical Engineering for
Springer Publishing; Associate Editor for the IEEE Transactions on
Neural Networks; on the editorial board of the IEEE Transactions on
Information Technology; editorial board of the IEEE Transactions On
Nano-bio-sciences, and the editorial board of the new journal
"Biomedical Engineering on-line".
She has served as Vice President for Conferences of the IEEE Neural
Networks Council. She was the 2003 President of the Neural Networks
Society; Chair of the IEEE Awards Board in 2003 and 2004. Currently she
is IEEE Director, Division X for 2005 and 2006.
Dr. Tzanakou has received several awards including: an Outstanding
Advisor Award in 1985 from IEEE, in 1992 the Achievement Award of the
Society of Women Engineers, in 1995 she was awarded the NJ Women of
Achievement Award for the application of neural networks to engineering
in medicine and biology. She is the recipient of the IEEE CIS
Meritorious Service Award for 2006.
Her research interests include Neural Networks, Information Processing
in the brain, Image and Signal Processing applied to Biomedicine,
Mammography, Telemedicine, Hearing Aids and electronic equivalents of
neurons. She has graduated over 40 Masters and PhDs and currently
supervises a number of graduate and undergraduate students.
========================================================================
=====
"Feature Extraction in Computational Intelligence"
An IEEE Computational Intelligence Society Distinguished Lecture
Speaker
=======
Professor Evangelia Micheli-Tzanakou
Department of Biomedical Engineering
Rutgers University
Piscataway, NJ, U.S.A
Day and Time
============
Monday, April 10, 2006
6:30 - 8:00 pm (refreshments will be served at 6:00 p.m.)
Location
========
Hart House, Debates Room (2nd floor front)
7 Hart House Circle
University of Toronto
Toronto, ON M5S 3H3 map - code HH
Organizer
The Signals & Computational Intelligence Joint Chapter
Contact
=======
Bruno Di Stefano
Abstract
========
One of the major problems a researcher faces is what is learned from
data obtained by various methods and different techniques. This tutorial
will discuss and compare topics such as: Statistical Advances and
Challenges, as well as Feature Extraction in Computational Intelligence
methodologies.
Often a simple model describes the data well, simply because the S/N
ratio is too small for detection of more complex structures-which for
example is the case with medical data involving human subjects. One has
a lot of variability both in intra- and inter-sets of data.
Some important Simple Tools that have been used for a long time are:
Linear Regression, Discriminant analysis, Principal Component Analysis etc.
In all of these, the size of the data set matters. Huge data sets create
memory problems. The question is how do we handle different data types
and how do we handle them? What if the data are correlated? What if we
have complex data structures?
In this lecture you will learn more about Computational Intelligence,
how to get to know your data and how to do Feature Extraction. Some
examples of "features" will be given and different feature extraction
methods will be discussed.
Biography
=========
Evangelia Micheli-Tzanakou is Professor II and Director of the
Computational Intelligence Laboratories ( www.cil.rutgers.edu) in the
Department of Biomedical Engineering at Rutgers and an adjunct professor
of the University of Medicine and Dentistry of New Jersey. Dr Tzanakou
was Chair of the BME Department for 10 years and established the
Undergraduate curriculum in the same. She is a Founding Fellow of AIMBE,
a Fellow of IEEE and a Fellow of the New Jersey Academy of Medicine. She
has published two books: "Supervised and Unsupervised Pattern
Recognition: Feature Extraction and Computational Intelligence" was
published by CRC Press in January 2000 and co-authored a book with S.
Deutsch on "Neuroelectric Systems", published by New York University
Press, in 1987. She has published over 250 scientific papers in
journals, conference proceedings and book chapters. She has also edited
several books and conference proceedings.
Dr. Tzanakou has established the first ever experimental Brain to
Computer Interface (BCI), using the ALOPEX algorithm, in 1974. This
method is now used for target optimization in Parkinson's disease.
ALOPEX has also been used in a wide variety of problems: signal
processing, image processing, pattern recognition, transportation and
many more.
Dr. Tzanakou is Book Series Editor in Biomedical Engineering for
Springer Publishing; Associate Editor for the IEEE Transactions on
Neural Networks; on the editorial board of the IEEE Transactions on
Information Technology; editorial board of the IEEE Transactions On
Nano-bio-sciences, and the editorial board of the new journal
"Biomedical Engineering on-line".
She has served as Vice President for Conferences of the IEEE Neural
Networks Council. She was the 2003 President of the Neural Networks
Society; Chair of the IEEE Awards Board in 2003 and 2004. Currently she
is IEEE Director, Division X for 2005 and 2006.
Dr. Tzanakou has received several awards including: an Outstanding
Advisor Award in 1985 from IEEE, in 1992 the Achievement Award of the
Society of Women Engineers, in 1995 she was awarded the NJ Women of
Achievement Award for the application of neural networks to engineering
in medicine and biology. She is the recipient of the IEEE CIS
Meritorious Service Award for 2006.
Her research interests include Neural Networks, Information Processing
in the brain, Image and Signal Processing applied to Biomedicine,
Mammography, Telemedicine, Hearing Aids and electronic equivalents of
neurons. She has graduated over 40 Masters and PhDs and currently
supervises a number of graduate and undergraduate students.
========================================================================
--
-- Bruno Di Stefano ____________________________________________________
***@sympatico.ca www3.sympatico.ca/nuptek
***@ieee.org
***@gmail.com www3.sympatico.ca/nuptek/BrunoDiStefano.html
________________________________________________________________________
-- Bruno Di Stefano ____________________________________________________
***@sympatico.ca www3.sympatico.ca/nuptek
***@ieee.org
***@gmail.com www3.sympatico.ca/nuptek/BrunoDiStefano.html
________________________________________________________________________