Subekshya Bidari, Department of Applied Mathematics, University of Colorado Boulder Evidence accumulation models of social foraging Foraging is often modeled as a sequence of patch-leaving decisions. The distribution of food in the environment is idealized as being contained in discrete patches (e.g., trees), and animals must decide when to depart...
Anthony Kearsley, Mathematical Analysis and Modeling Group, National Institute of Standards and Technology (NIST) Control of inward solidification in Cryobiology For many years, mathematical models that predict a cell’s response to encroaching ice has played an important role in developing cryopreservation protocols. It is clear that information about the cellular...
Erin Ellefsen and Lindsey Wong, Department of Applied Mathematics, University of Colorado Boulder Lyndsey’s Title: Mathematical Models of Wealth Distribution Through an Amenities-Based Theory Erin’s Title: Efficiently finding Equilibrium Solutions of Nonlocal Models in Ecology Lyndsey’s Abstract: The dynamics of wealth are not fully understood. In order to gain insight...
Nick Barendregt, Department of Applied Mathematics, University of Colorado Boulder Adaptive Decision Rules are Optimal in Simple Environments Decision-making in uncertain environments often requires adaptive forms of evidence accumulation, but less is known about the decision rules needed to achieve optimal performance. While recent studies of decision models in stochastic...
Sabina Altus, Department of Applied Mathematics, University of Colorado Boulder Mobility Informed Regional Modeling of the COVID-19 Pandemic in Colorado The trajectory of the COVID-19 pandemic has varied widely by region, and an understanding of these divergent timelines is of great import to local public health officials, as well as...
Dan Messenger, Department of Applied Mathematics, University of Colorado Boulder Weak-Form Sparse Identification of Nonlinear Dynamics with Applications to Cell Migration The weak-form sparse identification of nonlinear dynamics (WSINDy) algorithm for inferring nonlinear governing equations from noisy datasets significantly improves the accuracy and robustness to noise of strong-form methods. Furthermore,...
David Bortz and Nancy Rodriguez, Department of Applied Mathematics, University of Colorado Boulder Overview of Math Biology Research in the Applied Math Department David Bortz will give an overview of the math bio group here in the Applied Math Department. He will also describe his research group and our investigations...
Tahra Eissa, Department of Applied Mathematics, University of Colorado Boulder Normative decision asymmetries with symmetric priors but asymmetric evidence Decisions based on rare events are challenging because rare events alone can be both informative and unreliable as evidence. How humans should and do overcome this challenge is not well understood...
David Stearns, Department of Applied Mathematics, University of Colorado Boulder Dynamics and Analysis of Territorial Animals The ways animals form territories, interact with members of their own social group, and interact with members of other intraspecies social groups play a vital role in the maintenance of an ecosystem and in...
John Nardini, Department of Applied Mathematics, University of Colorado Boulder Data-driven modeling for noisy biological data and agent-based Models I will consider the problem of inferring the dynamics underlying biological data using two case studies in equation learning and topological data analysis. The math biology field presents several exciting challenges...
