Colloquia & Seminars

Colloquia & seminar talks are scheduled from 1:30pm - 2:45pm on Thursday each week and usually take place in DMSC 102, unless otherwise noted below. Speakers give 50-minute presentations on various mathematical and statistical topics.

If you would like to meet with a speaker, please contact math@unr.edu to schedule a meeting. To receive email announcements about future talks and events, please subscribe to our email list by sending an email to sympa@lists.unr.edu with a blank subject line and the main body 'subscribe mathstat-announce EmailAddress FirstName LastName'.

We look forward to your participation in our upcoming colloquia!

Colloquia and Seminar Talks Schedule
DateSpeakerInstitutionTitleRoom
Oct. 3, 2019 Frédéric Latrémolière University of Denver A topology on the class of quantum metric spaces
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Quantum metric spaces are noncommutative analogues of the algebras of Lipschitz functions over a (compact) quantum metric spaces. The quantum metric structure on C*-algebras enable the construction of a Gromov-type topology, and thus opens a new branch of noncommutative geometry. The main concern for this research project is the study of our new topology and how to extend ideas from metric geometry to quantum geometry. Moreover, the functional analytic perspective on Gromov-Hausdorff convergence suggests new ideas on defining the convergence of modules, group actions, and differential structures (in the form of convergence for spectral triples). We will discuss the current state of this research project.

DMS 102
Oct. 10, 2019 Alexander Hoover University of Akron From Nerve Net to Vortex Ring: A Computational Modeling Approach to Medusan Biomechanics
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In order for an organism to have a robust mode of locomotion, their neuromuscular organization must be adaptable in a changing environment. In jellyfish, the activation and release of muscular tension is governed by the interaction of pacemakers with the underlying motor nerve net that communicates with the musculature. This set of equally-spaced pacemakers located at bell rim alter their firing frequency in response to environmental cues, forming a distributed mechanism to control the bell's muscular contraction. The relative simplicity of the jellyfish nervous system presents mathematicians with the opportunity to examine an intriguing multi-scale, multi-physics system with many potential applications to soft-body robotics and tissue-engineered pumps. In this talk, we explore the control of medusan neuromuscular activation in with a model jellyfish bell immersed in a viscous fluid and use numerical simulations to describe the interplay between active muscle contraction, passive body elasticity, and fluid forces. The fully-coupled fluid structure interaction problem is resolved using an adaptive and parallelized version of the immersed boundary method (IBAMR). This model is then used to explore the interplay between the speed of neuromechanical activation, fluid dynamics, and the material properties of the bell.

DMS 102
Oct. 17, 2019 Fei Lu Johns Hopkins Data-informed stochastic model reduction for complex dynamics
Click for Abstract...

The need to develop reduced nonlinear statistical-dynamical models for complex dynamical systems arises in many applications such as geophysics, biology and engineering. The challenges come from memory effects due to the nonlinear interactions between resolved and unresolved scales, and from the difficulty in inference from discrete partial data.
We address these challenges by learning stochastic reduced models, in forms of nonlinear time series, that can account for the memory effects due to truncation/coarse-graining and the numerical errors due to large time-stepping. We show by examples that the stochastic reduced models can capture the key statistical and dynamical properties and can improve the performance of ensemble prediction in data assimilation. The examples include dissipative chaotic/stochastic ODEs and PDEs. We will discuss related open questions in inference and in theoretical understanding of the model reduction.

DMS 102
Oct. 24, 2019 Jun Song University of North Carolina at Charlotte Nonlinear dimension reduction for functional data
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In a recent decade, functional data analysis has attracted great attention since it is encountered frequently in contemporary data analysis such as the analysis in medical research, bioinformatics, and environmental science. However, it is difficult to derive theories of statistical methodology due to the infinite-dimensional nature in functional data. Motivated by the issue, in this talk, I will discuss methods of dimension reduction for functional data. We develop a nonlinear and additive version of principal component analysis for vector-valued random functions. This is a generalization of functional principal component analysis that allows the relations among the random functions involved to be nonlinear. The method is constructed via two additively nested Hilbert spaces of functions, in which the first space characterizes the functional nature of the data, and the second space captures the nonlinear dependence. In the meantime, additivity is imposed so that we can avoid high-dimensional kernels in the functional space, which causes the curse of dimensionality. Simulation results show that the new method outperforms functional principal component analysis when the relations among random functions are nonlinear. Application to the classification of hand-written digit data and related functional dimension reduction methods will be presented.

DMS 102
Oct. 31, 2019 Shmuel Friedland University of Illinois, Chicago The Collatz-Wielandt quotient  for pairs of nonnegative operators
Click for Abstract...

In this talk we consider two versions of Collatz-Wielandt quotient for a pair of nonnegative operators A,B that map a given pointed generating cone in the first space into  a given pointed generating cone in the second space. In the case the two spaces and the two cones are identical, and B is the identity operator this quotient one of the version is the spectral radius of A. In some applications, as commodity pricing, power control in wireless networks and quantum information theory, one needs to deal with the Collatz-Wielandt quotient for two nonnegative operators.  In this talk we treat the two important cases: a pair of rectangular nonnegative matrices and a pair completely positive operators. We give a characterization of minimal optimal solutions and polynomially computable bounds on the Collatz-Wielandt quotients.

DMS 102
Nov. 7, 2019 Jean Renault University of Orléans (France) TBA
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DMS 102
Nov. 14, 2019 Fares Qeadan University of Utah TBA
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DMS 102
Nov. 21, 2019 Artem Kotelskiy Indiana University, Bloomington TBA
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DMS 102
Nov. 28, 2019 Thanksgiving Thanksgiving No Colloquium
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Thanksgiving; no colloquium.

DMS 102
Dec. 5, 2019 TBA TBA TBA
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DMS 102
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DMS 102
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DMS 102
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DMS 102
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DMS 102
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DMS 102
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DMS 102
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DMS 102