Dr. Kwokleung Chan
Research Interests
My research interest is in development of machine learning techniques and
their application to the analysis of biological and biomedical data. I have
developed the variational Bayesian learning for independent component
analysis (ICA). ICA tries to locate independent axes within the data
cloud. It finds its use in modeling data density, describing data as
linear mixture of independent features and finding projections that may
uncover interesting structure in the data. The newly developed
variational Bayesian technique allows working directly on datasets having
high dimensions but small number of expensive examples. It
has been successfully applied to a glaucoma visual field dataset to
extract independent features. Recently, I have generalized the technique
to deal with data containing missing entries. Incomplete data is very
common in biomedical data due to cost in performing experiments and tests.
The generalized technique is now applied to a primate brain volumetric
dataset and very promising results are obtained.
Affliation:
-
Computational Neurobiology Lab, The Salk Institute
- Lee-Lab, INC, UCSD
Mailing Address:
The Salk Institute, CNL
10010 North Torrey Pines Road
La Jolla, CA 92037
USA
phone: (858) 453-4100, ext. 1463
fax: (858) 587-0417
kwchan@salk.edu