ºù«ÍÞÊÓƵ

Event Description: Mevin Hooten, Department of Statistics, Colorado State University De Motu Animalium: Modern Models for Animal Trajectories Advances in animal telemetry data collection techniques have served as a catalyst for the creation of statistical methodology for analyzing animal movement data. Such data and methodology have provided a wealth of...

Event Description: Eric Vance, Department of Applied Mathematics, ºù«ÍÞÊÓƵ Toward a Theory of Collaboration for Data Science The emerging field of Data Science is, by construction, an interdisciplinary, collaborative field. Statisticians, Mathematicians, and Computer Scientists work together (ideally) to create theoretically sound methods for domain experts and...

Event Description: Doug Nychka, National Center for Atmospheric Research (NCAR), ºù«ÍÞÊÓƵ, CO Large and non-stationary spatial fields: Quantifying uncertainty in the pattern scaling of climate models Pattern scaling has proved to be a useful way to extend and interpret Earth system model (i.e. climate) simulations. In the simplest case the...

Event Description: Ana Maria Rey, Joint Institute for Laboratory Astrophysics, ºù«ÍÞÊÓƵ Building with Crystals of Light and Quantum Matter: From clocks to computers Understanding the behavior of interacting electrons in solids or liquids is at the heart of modern quantum science and necessary for technological advances. However,...

Event Description: Xuemin Tu, Department of Mathematics, University of Kansas Nonoverlapping Domain Decomposition Methods for Saddle Point Problems Two widely used nonoverlapping domain decomposition methods BDDC (Balancing domain decomposition by constraints) and FETI-DP (Dual-primal finite element tearing and interconnecting) are studied for the systems of linear equations arising from the...

Event Description: Steffen Borgwardt, Department of Mathematical and Statistical Sciences, University of Colorado - Denver Operations Research in Land Exchange With geometric modeling techniques, one can represent the feasible solutions of problems in operations research as objects in high-dimensional space. The properties of these objects reveal information about the underlying...

Event Description: A weekly presentation of current research in the field of Applied Mathematics, suitable for most audiences. Location Information: Main Campus - Engineering Classroom Wing ( View Map ) 1111 Engineering DR ºù«ÍÞÊÓƵ, CO Room: 245 Contact Information: Name: Ian Cunningham Phone: 303-492-4668 Email: amassist@colorado.edu

Event Description: Will Kleiber, Department of Applied Mathematics, ºù«ÍÞÊÓƵ Multivariate Random Fields Most modern spatial datasets involve multiple variables that can exhibit complex cross-process dependencies. We review some classic approaches to building statistical models for multivariate spatial data, nearly all of which rely on specifying cross-covariance functions...

Event Description: Yi Qiang, The Earth Lab and Dept. of Geography, ºù«ÍÞÊÓƵ From Time to Time: Novel Representations of Time for Visual Analytics How to represent time is a fundamental question in many disciplines. Conventionally, time intervals are represented as linear segments in a one-dimensional space, which...

Event Description: Alireza Doostan, Department of Aerospace Engineering Sciences, ºù«ÍÞÊÓƵ Uncertainty Quantification Using Low-fidelity Data Realistic analysis and design of multi-disciplinary engineering systems require not only a fine understanding and modeling of the underlying physics and their interactions but also recognition of intrinsic uncertainties and their influences...