Advances in technology have enabled us to collect data from observations, simulations, and experiments at an ever-increasing pace. For the scientist to benefit from these enhanced data collecting capabilities, it is becoming clear that semi-automated techniques, such as the ones in data mining, must be applied to find the useful information in the data. Data Mining is a multi-disciplinary field, borrowing and enhancing ideas from diverse areas such as statistics, signal and image processing, image understanding, mathematical optimization, computer vision, and pattern recognition. It is rich in challenging mathematical problems, where the complexity and size of the data is matched only by the diversity of applications. Several recent workshops on the subject have indicated that this a field of active research with potential beneficiaries in areas such as astronomy, remote sensing, physics, bio-informatics, medical imaging, non-destructive evaluation, combinatorial chemistry, etc.
The goals for the workshop are:
Chandrika Kamath (Lawrence Livermore National Laboratory)
B. S. Manjunath (UCSB)
Padhraic Smyth (University of California at Irvine)