Complex Datasets and Inverse Problems: Tomography, Networks, and Beyond; Rutgers University - New Brunswick, NJ; October 21-22, 2005

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Abstract Prop ID: DMS-0534181 PI: Zhang, Cun-Hui PO: Shulamith T. Gross Institution: Rutgers University New Brunswick Title: Complex Datasets and Inverse Problems: Tomography, Networks, and Beyond The conference ``Complex Datasets and Inverse Problems: Tomography, Networks, and Beyond'' will be held October 21-22, 2005 at Rutgers University. The conference will focus on a number of important and emerging interdisciplinary areas of research, including medical tomography, networks, and biased data. Statistical tomography algorithms have been playing crucial roles in the development of medical imaging systems, from CAT, PET, SPECT to MRI. In fast functional MRI, brain functions are studied from data sets composed of multiple time series of incomplete Fourier transformation of the deoxy spin density of the brain. Networks are abundant around us: social, energy, traffic, communication, and computer are just some of the examples. Enormous amount of networks data have been collected in the information age we live in, but few statistical tools have been developed for analyzing them as they are typically governed by time-varying and mutually dependent communication protocols sitting on complicated graph-structured network topologies. Many prototypical applications in these and other important technologies can be viewed as statistical inverse problems with large, high-dimensional, and probably biased/incomplete data, which serve as the unifying ground for the conference. The conference will advance several important areas in statistics, including models and methodologies for complex datasets, inverse problems, imaging systems, networks, and incomplete and biased data. Cutting-edge developments of statistical models, methods, and algorithms will be discussed. The conference will have direct impact on a broad range of scientific applications outside the immediate realm of statistics. Examples include functional MRI and other medical imaging systems, telecommunication, energy, transportation, and social networks, network security, bioinformatics, epidemiology, and clinical trials. The conference is expected to attract researchers in different areas of applications, in medical imaging, telecommunications, bio-medical engineering, bioinformatics, epidemiology, and more. These will comprise both internationally renowned experts and graduate students or young researchers who wish to embark in these rapidly progressing interdisciplinary areas. Time will be generously allotted for informal discussion and fruitful exchange of ideas. Through these activities, the conference will play an important role in fostering new research partnership between young and senior participants and among researchers in different areas of applications. The conference will promote research activities, education, and participation of new investigators, graduate students, and researchers from under-represented groups. The proceedings of the conference have been arranged to be published as a volume in the Institute of Mathematical Statistics Monograph series. This publication will help disseminate widely the advances covered in the conference, especially among the researchers who are not able to attend the conference.