SAMSI hosted the Trends and Advances in Monte Carlo Sampling Algorithms Workshop, part of the Quasi-Monte Carlo and High-Dimensional Sampling Methods for Applied Mathematics (QMC) Program on the campus of Duke University from Dec. 11-15, 2017.
The workshop was attended by more than 100 experts in the fields of applied mathematics, statistics and machine learning for the purpose of exchanging ideas and advancing the broad area of sampling algorithms.
This event was the second workshop presented in the QMC program and featured how Monte Carlo sampling methods can be used to help optimize performance of machines and/or business and industrial processes. This complex methodology is widely used in physics, chemistry, mathematics and statistics, and is most useful when other methods fail due to the high dimensionality of the problem.
Participants enjoyed a week-long workshop that featured talks from innovative mathematicians from around the world. The talks focused on research being done in the field of Monte Carlo sampling and how these applications can be used to tackle real-world problems in business and industry.
The QMC program has ten working groups that were created in the QMC Opening Workshop in late August 2017. The working groups support research being done by applied mathematicians, statisticians and researchers across a wide variety of topics. The working groups will re-convene at the QMC Transition Workshop in May 2018 to discuss their findings and to develop collaborations between colleagues for future research.
The Trends and Advances Workshop is one of many ways in which SAMSI continues to promote the importance of applied mathematics, statistics and computational science. To see the research presented, visit the workshop webpage at: https://www.samsi.info/qmc-trends-and-advances.