Computational Symmetry

Speaker:	Dr. Yanxi LIU
		Robotics Institute and the Machine Learning Dept.
		Carnegie Mellon University

Title:		"Computational Symmetry"

Date:		Monday, 23 October 2006

Time:		3:00pm - 4:00pm

Venue:		Lecture Theatre G
		(Chow Tak Sin Lecture Theater, near lift nos. 25/26)
		HKUST

Abstract:

Symmetry is an essential mathematical concept, as well as a ubiquitous,
observable phenomenon in nature, science and art. Either by evolution or
by design, symmetry implies a potential structural efficiency gain that
makes it universally appealing. Much of our understanding and appreciation
of the world is based on the perception and recognition of shared or
repeated patterns, and so is our sense of beauty and style. Recognition
and categorization of symmetry and symmetry groups is the first step
towards capturing the essential skeleton of a problem, while at the same
time minimizing computational redundancy. Our research in the realm of
"Computational Symmetry" explores the use of symmetry and symmetry groups
in a wide range of applications in computer vision, computer graphics,
robotics and medical image analysis, including texture analysis, synthesis
and manipulation, human gait recognition, human identification, expression
classification, robotics assembly planning, computer aided diagnosis of
degenerative neurological disorders from structural MR images, and
quantification of the firing fields of grid cells in rat brains. The
central theme of this talk exposes a rapidly emerging research area, and
the promise and perils of making the idea of symmetry and group theory
computationally feasible for real world problems.


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Biography:

Yanxi LIU received her B.S. degree in physics/electrical engineering in
Beijing and her Ph.D. degree in computer science for group theory
applications in robotics from University of Massachusetts. Her
postdoctoral training was performed at LIFIA/IMAG, Grenoble, France. She
also spent one year at DIMACS (NSF center for Discrete Mathematics and
Theoretical Computer Science) with an NSF research-education fellowship
award. Currently, Dr. LIU is with both the faculty of Robotics Institute
(RI) of Carnegie Mellon University and the Machine Learning department of
CMU, and the Computer Science Engineering and Electrical Engineering
departments of Penn State University. She is also an adjunct associate
professor in the Radiology Department of University of Pittsburgh, and a
guest professor of Computer Science Department, Huazhong University of
Science and Technology in China. Dr. LIU's research interests span a wide
range of applications in computer vision, computer graphics, robotics and
computer aided diagnosis in medicine, with two central themes:
computational symmetry and discriminative subspace learning. With her
colleagues, Dr. LIU won the first place in the clinical science category
and the best paper overall at the Annual Conference of Plastic and
Reconstructive Surgeons for the paper "Measurement of Asymmetry in Persons
with Facial Paralysis." Dr. LIU chaired the First International Workshop
on Computer Vision for Biomedical Image Applications (CVBIA) in
conjunction with ICCV 2005 and co-edited the book: "CVBIA: Current
Techniques and Future Trends" (Springer-Verlag LNCS). Dr. LIU serves as a
reviewer/committee member/panellist for all major journals, conferences as
well as NIH/NSF panels on computer vision, pattern recognition, biomedical
image analysis, and machine learning. She had been a chartered study
section member for Biomedical Computing and Health Informatics at NIH. She
is a senior member of IEEE and the IEEE Computer Society.