Applied Math Seminar

Antibodies are the standard biomolecule for marking molecular structures and delivering drugs due to their specific binding capabilities. However, they are expensive to produce and their relatively large size prevents their easy traversal of bi-lipid membranes. Over the past 30 years, molecular recognition has also been achieved through the use of aptamers, short oligonucleotide sequences […]

Data coming from Monte Carlo experiments is often analyzed in the same way as data from more traditional sources.  The unique nature of Monte Carlo data, where it is easy […]

In this talk I will discuss a rather unique collection of tools and how they have been used to understand the spread of Influenza virus in the State of Montana.  With flu counts from each county over a 10 year period some patterns emerge, which explain some vectors of the disease spread.  Archetypal analysis then […]

Biological invasions often have outsized consequences for the invaded ecosystem and represent an interesting challenge to model mathematically. Landscape heterogeneity, non-local or time-dependent spreading mechanisms, coarse data, and air or […]

In water-limited regions, competition for water resources results in the formation of vegetation patterns; on sloped terrain, one finds that the vegetation typically aligns in stripes or arcs. The dynamics […]

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Abstract of Leandro Recova's talk

We propose a regularization and variable selection method, named arbitrary rectangle-range generalized elastic net (ARGEN). It can be applied in high dimensional sparse linear regression models. We propose an algorithm […]

Nonlocal theories have emerged with powerful models and methods to analyze and predict complex phenomena. Different versions of nonlocal operators have been proposed, each with its advantages and challenges. In […]

This talk focuses on using a multiwavelet representation of the discontinuous Galerkin (DG) approximation for trouble cell indication. The multiwavelet representation is related to the jumps in the (derivatives of) […]

Online social media networks have become extremely influential sources of news and information. Given the large audience and the ease of sharing content online, the content that spreads on online social networks can have important consequences on public opinion, policy, and voting. To better understand the online content spread, mathematical modeling of opinion dynamics is becoming […]