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Mathematical Challenges and Opportunities in Sensor Networking

January 8 - 12, 2007

Schedule and Presentations

Program Poster PDF

Hotel Accommodation and Air Travel

Organizing Committee:

Richard Baraniuk (Rice University, Electrical and Computer Engineering)
Mark Hansen (UCLA, Department of Statistics)
Robert Nowak (University of Wisconsin-Madison, Electrical and Computer Engineering)

Scientific Overview:

Sensor networking is an emerging technology that promises an unprecedented ability to monitor our world via spatially distributed networks of sensor nodes. The nodes may sense the physical environment in a variety of modalities, including acoustic, seismic, thermal, and infrared, or may be deployed throughout engineered systems such as the Internet for the purposes of monitoring or surveillance. A wide range of applications of sensor networks have been envisioned, including environmental monitoring, homeland security, and medical diagnostics. While the practically unlimited range of applications of sensor networks is quite evident, our current understanding of their design and management is far from complete. Since sensor networks collect data in a spatially distributed fashion, data analysis problems in sensor networks present a distinct new challenge. In addition to all the common issues associated with data analysis and modeling, limited energy and/or bandwidth resources place a very high cost on the sharing and fusing data within the network. Consequently, new theories and methods for data analysis, modeling, and communication will play a central role in the development of this exciting new field.

There will be two explicit goals of the IPAM workshop. The first goal is to introduce sensor networking to mathematicians and scientists who work in the related areas but are not currently involved in the field. The nascent research community in sensor networking has already drawn heavily on a variety of mathematical theories and techniques originating from areas such as signal processing, statistics, stochastic modeling, machine learning, and computer science, and we anticipate that the future directions and successes in this field will be largely shaped by a healthy and vibrant interdisciplinary approach to the research. The second goal is to outline future directions for the mathematical and statistical development in the theory and methods employed in sensor networking. This will be achieved by complementing technical and overview presentations “brainstorming” sessions in which mathematicians, engineers, and computer scientists will be brought together in groups to define the big issues and the possible directions of research that might resolve them. Since sensor networking is still a very new field, with only a handful of fielded systems in existence, now is an ideal time to attract mathematical experts from all areas to shape and contribute to the future of this unique application domain. IPAM is uniquely positioned to host this workshop due to its tradition of bringing together mathematicians and technologists, and especially due to the presence of the Center for Embedded Networked Systems (CENS) at UCLA, which is one of the premier sensor networking research groups in the world.

Speakers

Nigel Boston (University of South Carolina)
Jim Clark (Duke University)
Mark Coates (McGill University)
Hugh Durrant-Whyte (University of Sydney)
Michelle Effros (California Institute of Technology)
John Fisher (Massachusetts Institute of Technology)
Michael Gastpar (UC Berkeley)
Alan Gelfand (Duke University)
Mark Hansen (UCLA)
Tom Harmon (University of California, Merced (UC Merced))
Alfred Hero (University of Michigan)
P. R. Kumar (University of Illinois at Urbana-Champaign)
Mingyan Liu (University of Michigan)
Upamanyu Madhow (UC Santa Barbara)
Barbara Minsker (University of Illinois at Urbana-Champaign)
Urbashi Mitra (University of Southern California (USC))
Jose Moura (Carnegie-Mellon University)
Richard Murray (California Institute of Technology)
Robert Nowak (University of Wisconsin-Madison)
Greg Pottie (UCLA)
Venkatesh Saligrama (Boston University)
Akbar Sayeed (University of Wisconsin-Madison)
Anna Scaglione (Cornell University)
Sergio Servetto (Cornell University)
Mani Srivastava (University of California, Los Angeles (UCLA))
John Stankovic (University of Virginia)
Venugopal Veeravalli (University of Illinois at Urbana-Champaign)
Lin Xiao (Microsoft Research)

Contact Us:

Institute for Pure and Applied Mathematics (IPAM)
Attn: SN2007
460 Portola Plaza
Los Angeles CA 90095-7121
Phone: 310 825-4755
Fax: 310 825-4756
Email: ipam@ucla.edu
Website: http://www.ipam.ucla.edu/programs/sn2007/


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