How to process very large volumes of high-dimensional data and discover vital information contained in those data are among the most challenging issues in computational biomedicine. These data could be experimental data in protein structures, spatial-temporal data in medical imaging, and DNA sequences in human genome database, to name just a few. Mathematical modeling and computer technologies are playing important roles in this investigation. We are particularly interested in discrete mathematical problems and modeling in high-dimensional data clustering algorithms, high-dimensional data mining techniques, and high-dimensional spatial-temporal data storage for fast information retrievals.
This workshop provides a forum for researchers and practitioners to meet and exchange research ideas and interests, as well as to discuss new directions and identify open problems in the development and deployment of this area.