Meetings/Workshops on Applied Mathematics (in general) in Canada

The Fields Institute for Research in Mathematical Sciences

The focus of this mini-symposium is particularly on DG applications. In fact, a more recent trend is nowadays emerging in the scientific literature, where a much larger number of applications, for which a DG formulation can be supplied, has been brought to the light, so that theoretical results, algorithms, methods and even software tools, initially developed for one specific application, can be adapted, or simply reused, for other applications. Sensors capable to give information about distances are frequently used in these applications, even if their nature often differs from the notion of "sensor" historically used in works on sensor network localization, while the temporal (or dynamical) factor is taking more and more importance. Our list of invited speakers reflects this heterogeneity of applications, with a mathematical background that remains essentially coherent.

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

Fluid-driven crack propagation is the process by which pressurized fluid drives cracks through solid materials. Such a process is not only central to hydraulic fracture stimulation of oil and gas wells, but also it describes movement of molten rock through the Earth’s crust and water through the subsurface of glacial ice sheets. Hence, there is significant, and hitherto relatively untapped, potential for multidisciplinary investigation. Furthermore, the underlying mathematical problem is challenging even for simple propagation geometries and ignoring variability in material properties of the rock and/or ice sheet. When realistic variability and complexity is considered, the problem exceeds the capabilities of current computer simulation tools. To address these concerns, the objective of this workshop is to convene a BIRS Workshop of Applied Mathematicians, Geo-Scientists, and Engineers from Academia and Industry to accelerate the development of the state-of-the-art tools to analyze the evolution of fluid-driven cracks that propagate in complex solid media.

Courses and Events for Math Students and Early Career Researchers,    Geophysics and Geology

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

We will aim to create new mathematical models of complex fluids that can bridge length and time scales, and study novel ways to model entanglement of polymers and filaments. We stress that the novelty of this workshop consists not only in bringing together an interdisciplinary array of scientists, but bridging the gap between what has been traditionally catalogued as pure and applied mathematics.

Courses and Events for Math Students and Early Career Researchers,    Condensed Matter Physics and Materials

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

The mathematics of optimal transport (OT) has grown to become a unifying theme in many scientific disciplines, from solving purely mathematical problems of analysis, geometry, and partial differential equations to developing revolutionary new methods in economics, statistics, machine learning and artificial intelligence. In the last decade, the impact of optimal transport in the study of geometry was highlighted by two Fields medals (Villani 2010, Figalli 2018). On the other hand, OT has established itself as a viable alternative to classical maximum likelihood based methods in statistics and data science. Other notable applications include generative adversarial network (GAN) in machine learning (Wasserstein GAN), new applications to stem cell biology, and economic applications such as generalizations of the Nobel prize winning Gale-Shapley algorithm, online auctions, and option pricing.

Courses and Events for Math Students and Early Career Researchers,    General Mathematical Research and Multidisciplinary Events

Department of Mathematics & Statistics and the Department of Supply Chain & Business Technology Management of Concordia University in Montreal

In keeping with the long tradition of previous decennial conferences (starting in 1971), this convention is dedicated to all areas of statistical sciences. In addition to the traditional theoretical/applied areas, interdisciplinary research would be encouraged and promoted including major theme areas Applied Statistics, Big Data, Bioinformatics, Biostatistics, Computational Statistics, Data Mining, Data Science, Demography, Econometrics, Health Statistics, Model Selection and Validation, Social Statistics, Supply Chain, Survival Analysis, Stochastic Methods in Ecology, Finance and Engineering.

The 2021 conference will be held on a virtual platform.

The Fields Institute for Research in Mathematical Sciences

Many biological species exhibit range shifts: some spread after being introduced into new environments, others follow their preferred climatic conditions under global change. Recent theoretical and empirical results highlight the importance of evolutionary change in these ecological processes. Specifically, they show that evolution can be the driving mechanism behind the range expansion of plants and animals, and that scientists may be underestimating how quickly species can move. However, the ecological and evolutionary processes involved in range expansions have mostly been studied separately, and despite recent advances in theory and experiments, making predictions about the speed of expansion is inherently difficult. The goal of this workshop is to convene mathematicians, modellers, and empiricists to exchange recent results on eco-evolutionary dynamics in species' range expansions and to develop novel mathematical frameworks to address important questions such as the relative contributions of ecological processes, evolutionary processes and environmental conditions on the speed and the variation in speed of range expansion.

Modeling and Simulation,    Systems Biology and Computational Biology

The Fields Institute for Research in Mathematical Sciences

How can we obtain scientic benefits from statistical analysis of sensitive data, without compromising the privacy of the individuals who contribute their data? The past decade has seen rapid progress on this question due to the emergence of a mathematically rigorous privacy framework known as differential privacy. Informally, differential privacy provides a robust individual privacy guarantee, ensuring that no adversary, regardless of their capabilities, can learn much more about an individual user than they could have learned had that user's data never been collected.

Information Security and Information Privacy,    Cryptography, Blockchain and Information Security