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Manuchehr Aminian, Department of Mathematics, Colorado State University Using mathematical tools to understand the immune system How soon after exposure can we identify that you're infected with the flu? Can this be done prior to the onset of symptoms? Why do some animals tolerate bacterial infections better than others? It...

Steve Sain Jupiter Intelligence, Â鶹ӰԺ CO Data Science @ Jupiter In 2017, the US faced over $300 billion in loses from hurricanes, severe weather, flooding, drought, fire, etc. These national catastrophes are placing an increasing burden on the public and are projected to worsen in the future. Jupiter Intelligence provides...

Andreas Kloeckner Department of Computer Science, University of Illinois Fast Algorithms for the Evaluation of Layer and Volume Potentials I will present new, asymptotically fast algorithms with high-order error bounds for the evaluation of layer and volume potentials in two and three dimensions. The efficient evaluation of both types of...

Rebecca Morrison Department of Computer Science, Â鶹ӰԺ Representing model error in reduced models of interacting systems In many applications of interacting systems, we are only interested in the dynamic behavior of a subset of all possible active species. For example, this is true in combustion models (many...

Catherine Sulem Department of Mathematics, University of Toronto Bloch theory and spectral gaps for linearized water waves We consider the movement of a free surface of a two-dimensional fluid over a variable bottom. We assume that the bottom has a periodic prole and we study the water wave system linearized...

John Harlim Departments of Mathematics and Meteorology, Penn State University Manifold learning based computational methods Recent success of machine learning has drawn tremendous interests in applied mathematics and scientific computations. In this talk, I will discuss recent efforts in using manifold learning algorithms (a branch of machine learning) to do...

Matthew Norman, Oak Ridge National Laboratory Fluids algorithms from a High Performance Computing Perspective Numerical approximations to Partial Differential Equations have provided diverse benefits to society over the years. Their applications in simulation codes have weathered a number of large changes in computing as well, from the original vector machines...

Jennifer Ryan Department of Applied Mathematics and Statistics, Colorado School of Mines Superconvergence Extraction: How to do it? When is it applicable? Many numerical simulations produce data that contains hidden information. This hidden information can be exploited to create even more accurate representations of the data by appropriately constructing convolution...

Henry Adams Department of Mathematics, Colorado State University An introduction to applied topology This talk is an introduction to computational topology, as applied to data analysis and to sensor networks. The shape of a dataset often reflects important patterns within. Two such datasets with interesting shapes are a space of...

Adrianna Gillman Department of Applied Mathematics, Â鶹ӰԺ An efficient and high order accurate direct solution technique for variable coefficient elliptic partial differential equations For many applications in science and engineering, the ability to efficiently and accurately approximate solutions to elliptic PDEs dictates what physical phenomena can be...