Conference on the Foundations of Computational Mathematics

North Carolina State University, Raleigh NC

Investigators

Abstract

This proposal seeks support to increase the participation of US researchers to the Conference on the Foundations of Computational Mathematics (FoCM) which will be hosted by the Budapest University of Technology and Economics in Hungary between July 4-14, 2011. The conference is the seventh in a sequence of international meetings organized by the Society for the Foundations of Computational Mathematics. The meetings are held every three years and the preceding ones have been held in different countries in North and South America and Europe. The NSF funding will cover the travel costs (airfare and partial subsistence support) for 30 conference participants who are US citizens/permanent residents, or work/study at a US institution. The supported participants will be predominantly students and young researchers from the US, but the organizers expect to also cover the travel and subsistence expenses of some senior participants. NSF funding to support travel and other participant costs for approximately 30 junior researchers and graduate students. The conference organizers have been traditionally and continue to be dedicated to attracting young participants and participants from under-represented groups and providing valuable opportunities for networking with the leaders of the disciplines. The conference will facilitate the flow of ideas between the theoretical computer science, computational and core mathematics communities. The research areas represented at the conference span a diverse array of topics on the broad interface between mathematics and contemporary computation. The agenda of the conference includes 20 workshops on a broad array of topics including Approximation theory, Computational harmonic analysis, Computational algebraic geometry, Stochastic computation, Computational dynamics, Computational number theory, Combinatorics and intractability in computation, Discrete Optimization, Continuous Optimization, Learning theory, Information-based complexity, etc.