SUNMONTUEWEDTHUFRISAT
Conferences, Lectures, & Seminars
Events for December
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CS Colloquia: Aspects of Information Fusion and Computational Discovery for Bioinformatics
Tue, Dec 04, 2007 @ 04:00 PM - 05:30 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Title: Aspects of Information Fusion and Computational Discovery for BioinformaticsSpeaker: Dr. Raj Acharya (Penn State University)ABSTRACT:
Information fusion involves combining information from several different
sources to make informed decisions. It exploits the notion that 'the fused
whole is more than the sum of its parts'. The field of bioinformatics is
replete with multiple information sources such as microarray data, sequence
data, conservation information, textual literature, and multiple data banks.
This provides an excellent opportunity to exploit the techniques of
information fusion in the field of bioinformatics.In this talk, we will present information fusion algorithms for computational
discovery in bioinformatics.BIO:
Raj Acharya obtained his Ph.D. from the Mayo Graduate School of
Medicine/University of Minnesota in 1984. Since then, he has worked as a
research scientist at the Mayo Clinic and at GE (Thomson)-CGR in Paris,
France. He has also been a Faculty Fellow at the Night Vision Laboratory in
Fort Belvoir in Washington, D.C. and has been a NASA-ASEE Faculty Fellow at
the Johnson Space Center in Houston, TX. He is currently the Head of Computer
Science and Engineering Department at Penn State. During his tenure, the CSE
department has been ranked amongst the top 10 CS departments in the country.His main research thrusts are in the general area of bioinformatics and
biocomputing. He is the architect of the PCABC Cancer Bioinformatics
Datawarehouse project. He works on using information fusion techniques for
genomics and proteomics. He is also developing fractal models for the DNA
replication and transcription sites. He is associate editor of IEEE/ACM
Transactions on Computational Biology and Bioinformatics. He is also the
cochair of the IAPR Technical Committee on Pattern Recognition for
Bioinformatics. His research work has been featured among others in
Businessweek, Mathematics Calendar, The Scientist, Diagnostic Imaging,
Biomedical Engineering Newsletter, and Drug Design.Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: CS Colloquia
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CS Colloquia: Next Generation Dynamic Spectrum Systems
Thu, Dec 06, 2007 @ 11:00 AM - 12:30 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Title: Next Generation Dynamic Spectrum SystemsSpeaker: Prof. Heather Zheng(UCSB)ABSTRACT:
Today's static spectrum assignment policy has led to a critical spectrum
shortage. While innovative wireless networks such as WiMAX are denied
from spectrum access, the majority of existing networks use only 10-15%
of their assigned spectrum. To reuse "wasted" spectrum, the recent
proposal on dynamic spectrum access allows unlicensed (secondary) users
to opportunistically utilize unused licensed spectrum on a
non-interfering basis. This "creates" new capacity and commercial value
from existing under-utilized spectrum.While it shows great promise, the technology underlying dynamic spectrum
systems is still in its infancy. Issues in wireless communications and
networking, once addressed in the context of fixed spectrum assignment,
offer new research challenges in the realm of dynamic spectrum systems.
In this talk, we describe some existing and on-going efforts on
dynamic spectrum systems. We begin by describing distributed algorithms
for secondary users to access spectrum fairly and efficiently. We
introduce (1) a distributed coordination approach where devices
coordinate to adapt spectrum assignment over topology variations, and
(2) a light-weight rule-based solution that requires minimum
communication overhead. We then present a dynamic spectrum auction
framework that addresses the impact of economic issues. We conclude by
summarizing this work in context, and discussing current and future
directions in combining these results with higher layer mechanisms, and
applying cross-layer design to produce an end-to-end programmable and
adaptive network.Additional information about this research can be found at
http://link.cs.ucsb.edu.BIO:
Since August 2005, Heather Zheng has been an assistant professor at
Department of Computer Science, University of California, Santa Barbara.
Her research area includes wireless networking and communications, and
multimedia computing. She currently focuses on Cognitive Radios and
dynamic spectrum networks. Her research on Cognitive Radios was selected
as one of the 10 Emerging Technologies of 2006 by MIT Technology Review
Magazine, and the Best Student Paper in IEEE DySPAN 2007. Dr. Zheng was
named as the MIT Technology Review's Top 35 Innovators under the age of
35 in 2005. She also received 2006 World Technology Award (top 5 in
communication), 2002 Bell-Labs President's Gold Award, 1998-99 George
Harhalakis Outstanding Graduate Student Award from University of
Maryland, College Park. Dr. Zheng received her Ph.D. from University of
Maryland, College Park in 1999 and then joined wireless research lab,
Bell-Labs, Lucent Technologies. She then moved to Microsoft Research
Asia as a project lead in March 2004 and later joined UCSB.Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: CS Colloquia
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CS Colloquia: Interactive and Intuitive Appearance Design
Tue, Dec 11, 2007 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Title: Interactive and Intuitive Appearance Design Speaker : Professor Fabio Pellacini - Dartmouth CollegeABSTRACT:
The appearance of objects comes from the interaction of scene lighting and
surface materials, whose careful definition is necessary to achieve the
remarkable sophistication of today's synthetic imagery.
Currently, appearance design is one of the remaining roadblocks for a
ubiquitous use of computer-generated imagery, since slow user feedback and
cumbersome user interfaces make the process significantly time consuming for
expert designers, and beyond the reach of novices.In this talk, I will present our recent results in rendering accurate
lighting for complex environments where we achieve interactivity by
developing new approximation algorithms that can take advantage of inherent
properties of lighting and of today's commodity hardware architectures.
These algorithms completely change the workflow of artists from an offline
to a fully interactive process.
I will also show results from algorithms that build on this interactivity to
support intuitive user interfaces for appearance design that drastically
simplify the time require for designing appearance.BIO:
Fabio Pellacini is an assistant professor in computer science at Dartmouth
College. His research focuses on algorithms for interactive, high-quality
rendering of complex environments and for artist-friendly material and
lighting design to support more effective content creation.Prior to joining academia, Pellacini worked at Pixar Animation Studios on
lighting algorithms, where he received credits on various movie productions.Pellacini received his Laurea degree in physics from the University of Parma
(Italy), and his M.S. and Ph.D. in computer science from Cornell University.Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: CS Colloquia
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CS Colloquia: Mechanism Design, Machine Learning, and Pricing Problems
Tue, Dec 11, 2007 @ 04:00 PM - 05:30 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Title: Mechanism Design, Machine Learning, and Pricing ProblemsSpeaker: Maria-Florina Balcan(CMU)ABSTRACT:
In this work, we make an explicit connection between machine learning and
mechanism design. In doing so, we obtain a unified approach for considering a
variety of profit maximizing mechanism design problems, including many that
have been previously considered in the literature. In particular, we use
techniques from sample complexity in machine learning theory to reduce
problems of incentive compatible mechanism design to standard algorithmic
questions. We apply these results to a wide variety of revenue-maximizing
pricing problems, including the problem of auctioning a digital good, the
attribute auction problem, and the problem of item pricing in unlimited supply
combinatorial auctions. From a learning perspective, these settings present
several unique challenges: the loss function is discontinuous and asymmetric,
and the range of bidders' valuations may be large. This talk is based on joint work with Avrim Blum, Jason Hartline, and Yishay
Mansour.BIO:
Maria-Florina Balcan is a Ph.D. candidate at Carnegie Mellon University under
the supervision of Avrim Blum. She received B.S. and M.S. degrees from the
Faculty of Mathematics, University of Bucharest, Romania. Her main research
interests are Computational and Statistical Machine Learning, Computational
Aspects in Economics and Game Theory, and Algorithms. She is a recipient of
the IBM PhD Fellowship.Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: CS Colloquia
