Graph-theoretic approaches to data analysis
- I am a Ph.D. candidate in the Cognitive and Neural Systems department at
Boston University, expecting to defend my thesis in August (i.e., 2003).
My research has focused on the application of analogies between graph
theory and vector calculus to the analysis of data associated with the
node set of a graph. Specifically, this research was carried out in the
context of biologically inspired, space-variant machine vision, although
it is not tied to any notion of dimension, and therefore applies to
problems in data clustering, computer graphics, etc. Since our department
was founded by Stephen Grossberg, I have necessarily had a lot of exposure
to neural networks, as well. Our lab webpage (Computer Vision and
Computational Neuroscience Laboratory) is at http://eslab.bu.edu, if
anybody is interested (feedback is always welcomed).
Since my graduation date is rapidly approaching, I was wondering if
anybody reading this list was aware of job opportunities that might fit my
experience, had any constructive criticism of my resume or any general
advice in pursuing my job hunt. I have attached my resume to this mail in
a .pdf format. My career interests span a large space, including
traditional signal processing, pattern analysis, robotics, medical
imaging, biotechnology, and machine vision, among others.
I have submitted two papers and am currently in the final stages of
preparing four others. In addition, I have written a MATLAB toolbox that
manipulates graphs and incorporates existing graph-based processing
algorithms, as well as the new algorithms I have developed in the course
of my thesis work. I am willing to provide preprints of any of these
documents (including my thesis), as well as the software.
Thank you very much,
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