Seminars

Mathematical Biology Seminar - Erin Ellefsen

Oct. 19, 2020

Erin Ellefsen, Department of Applied Mathematics, University of Colorado Boulder Nonlocal Models in Ecology Nonlocal models can be very useful to describe some phenomena in Ecology. However, they also pose both analytical and computational challenges. We investigate territory development of meerkats by studying a system of nonlocal continuum equations. We...

APPM Department Colloquium - Aleksandar Donev

Oct. 16, 2020

Aleksandar Donev, Professor of Mathematics, Courant Institute of Mathematical Sciences, New York University Numerical Methods for Inextensible Slender Fibers in Stokes Flow Every animal cell is filled with a cytoskeleton, a dynamic gel made of inextensible fibers, such as microtubules, actin fibers, and intermediate filaments, all suspended in a viscous...

Complex/Dynamical Systems Seminar - Perrin Ruth

Oct. 15, 2020

Perrin Ruth, Department of Applied Mathematics, University of Colorado Boulder Dodge and survive: modeling the predatory nature of dodgeball The analysis of games and sports as complex systems can give insights into the dynamics of human competition, and has been proven useful in soccer, basketball, and other professional sports. In...

APPM Department Colloquium - Bernard Deconinck

Oct. 9, 2020

Bernard Deconinck, Professor and Chair of Applied Mathematics, University of Washington Pole dynamics of solutions of integrable equations Kruskal (1974) suggested that the dynamics of solutions of the KdV equation could be understood by examining how their pole singularities (complex x, real t) interact. I will review a biased history...

Complex/Dynamical Systems Seminar - Juan Restrepo

Oct. 8, 2020

Juan Restrepo, Department of Applied Mathematics, University of Colorado Boulder Using machine learning to assess short term causal dependence and infer network links The general problem of determining causal dependencies in an unknown time-evolving system from time series observations is of great interest in many fields. Examples include inferring neuronal...

Mathematical Biology Seminar - Lewis Baker

Oct. 5, 2020

Lewis Baker, Department of Applied Mathematics, University of Colorado Boulder Inference of Diffusion Coefficients from Single Molecule Trajectories Single particle tracking (SPT) enables experimentalists to observe the movement of individual molecules in various experimental contexts. As this field advances, the questions posed by researchers require increasingly nuanced analyses of the...

APPM Department Colloquium - Philippe Naveau

Oct. 2, 2020

Philippe Naveau, Laboratoire des Sciences du Climat et de l'Environnement, IPSL-CNRS, France Detecting changes in multivariate extremes from climatological time series Joint work with Sebastian Engelke (Geneva University) and Chen Zhou (Erasmus University Rotterdam) Many effects of climate change seem to be reflected not in the mean temperatures, precipitation or...

APPM Department Colloquium - Julie K. Lundquist

Sept. 25, 2020

Julie K. Lundquist, Dept. of Atmospheric and Oceanic Sciences and Fellow, Renewable and Sustainable Energy Institute at University of Colorado, Boulder Turbulence to turbine wakes: challenges in the atmospheric science of wind energy (that could benefit from applied mathematicians) As the world moves away from fossil fuels and towards more...

Complex/Dynamical Systems Seminar - Nathan Duignan

Sept. 24, 2020

Nathan Duignan, Department of Applied Mathematics, University of Colorado Boulder Non-Existence of Invariant Surfaces Transverse to Foliations Of fundamental importance to the qualitative understanding of dynamical systems are invariant manifolds. In this presentation we will explore a recent paper of MacKay on a condition which guarantees the non-existence of invariant...

Mathematical Biology Seminar - Daniel Messenger

Sept. 21, 2020

Daniel Messenger, Department of Applied Mathematics, University of Colorado Boulder Data-Driven Model Selection using Weak SINDy with Applications to Spatiotemporal Problems in Biology The task of identifying governing equations to match observed phenomena is crucial to understanding and predicting the behavior of complex systems for which derivation of models from...

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