Workshop on Multilevel Computational Methods and Optimization

This grant supports travel of US researchers to attend the workshop on 'Mutilevel methods and Optimization' from April 29 to May 2, 2013, at the Weizmann Institute of Science in Rehovot, Israel. The planned talks and panel discussions will cover classical problems such as partial differential equations, together with modern tasks such as web search and data mining. Speakers and participants in the workshop come from a variety of disciplines, including physics, biology, chemistry, economics, environment and earth sciences, computer science and engineering. A special two-hour panel 'Challenges in Multilevel Computation: where should we be directing our efforts and our graduate students?' is planned for the second day.

Multilevel solution methods for simulation and optimization problems over very large number of variables is central and important to virtually all disciplines in the sciences and engineering. These methodologies are very powerful because they exploit the fact that most computational problems have multiple scales. This notion of multiple scales may take on many different guises, including time and space, pixels, particles, proteins, or web-pages. This multiplicity and disparity of scales is an essential source of computational complexity. The multilevel algorithms address the problem under consideration at a hierarchy of scales, typically treating each with a method that is local to that particular scale. The proposed workshop will bring together junior researchers and world-class experts, mainly from North America, Western Europe, and Israel, to exhibit and discuss their recent research on multilevel computational methods for simulation and optimization in a wide variety of topics and applications. Together, the diverse backgrounds of the participants in the workshop and the planned activities are expected to expose new research directions in multilevel computational methods and to identify the most pressing challenges in this diverse field.