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Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

As the world population lives more and more in large urban areas, and as we are about to reach critical levels of greenhouse gases concentrations, the changing atmospheric composition has increasingly important economic, environmental and health impacts. It is thus becoming important to better quantify air pollution and its sources, using all the available information from observations to computer models, and use it in a synergistic way to maximize the information content – this is what data assimilation and inverse modeling aim for. This interdisciplinary workshop brings together engineers and researchers from numerical mathematics, statistics, and environmental sciences, to develop and innovate on the assimilation and inverse methods to address the specific issues related to atmospheric composition and chemistry. It will also be a forum to train new scientists in this emerging field, and to promote the research towards new operational monitoring products.

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

Cells are the fundamental building blocks of life. Recent advancement in biotechnology has allowed us to peek inside this every cell for better understanding of biology and human disease. Single-cell technology also generates big and complex data and brings about new data science challenges for computational and life scientists. The objective of this workshop is to bring together international leaders in diverse disciplines including mathematical, statistical, computational, biological and medical in a collaborative atmosphere to develop the collaborative capacity that will tackle various underlying data science challenges in single-cell research.

Molecular Biology,    Systems Biology and Computational Biology

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

In this workshop, we will explore how the research realms of generative modelling and 3D neural representations can benefit from each other, as well as explore novel applications in different areas of science and technology.

Modeling and Simulation,    Neural Networks and Artificial Intelligence, Machine Learning

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

What could be a bigger source of "big data" than the entire Universe? Researchers in statistics and computer science are developing new methods to analyse the "big data" that companies and governments want to understand. To test out these methods they need big datasets that everyone can share --- and new astronomical telescopes just happen to be gearing up to generate observations of billions of stars and galaxies that fit the bill. Insights from statistics will help astrophysicists to get the most out of these observations. The Astrostatistics 2023 workshop will bring together statisticians and astrophysicists to learn the technical languages of the two fields and identify how to work together to combine the excitement of space with big data.

Astronomy, Astrophysics and Cosmology,    Probability and Statistics, Game Theory