| Data science approaches to quantify key characteristics of SARS-CoV-2 outbreaks Ruian Ke Theoretical Biology and Biophysics, Los Alamos National Laboratory, New Mexico |
| Student-Integrated Research in Object Data Analysis Leif Ellingson Department of Mathematics and Statistics, Texas Tech University |
The Statistics seminar group encourages attendance of this Departmental T&P Colloquium and may be attended virtually at 3:30 PM (UT-5) via this Zoom link.
Meeting ID: 939 5734 3379
Passcode: Ellingson
| The geometric cobordism hypothesis and locality of extended field theories Dmitri Pavlov Department of Mathematics and Statistics, Texas Tech University |
The talk will include the necessary background on topology and field theory.
The Geometry and Topology and Quantum Homotopy seminar groups encourage attendance of this Departmental T&P Colloquium and may be attended virtually at 3:00 PM (UT-5) via this Zoom link.
Meeting ID: 956 3178 2128
Passcode: Pavlov
| Folly and Fantasy in Finance Dilip Madan School of Business, University of Maryland |
This Departmental Colloquium is sponsored by Mathematical Finance and may be attended at 2 PM CDT (UT-5) via this Zoom link.
Meeting ID: 998 7917 6042
Passcode: 800990
| Lie-Poisson Neural Networks (LPNets): Data-Based Computing of Hamiltonian Systems with Symmetries Vakhtang Putkaradze Mathematical and Statistical Sciences, University of Alberta |
We provide a solution to the problem of data-based computation of Hamiltonian systems utilizing symmetry methods. Many Hamiltonian systems with symmetry can be written as a Lie-Poisson system, where the underlying symmetry defines the Poisson bracket. For data-based computing of such systems, we design the Lie-Poisson neural networks (LPNets). We consider the Poisson bracket structure primary and require it to be satisfied exactly, whereas the Hamiltonian, only known from physics, can be satisfied approximately. By design, the method preserves all special integrals of the bracket (Casimirs) to machine precision. LPNets yield an efficient and promising computational method for many particular cases, such as rigid body or satellite motion (the case of SO(3) group), Kirchhoff's equations for an underwater vehicle (SE(3) group), and others.
Joint work with Chris Eldred (Sandia National Lab), Francois Gay-Balmaz (CNRS and ENS, France), and Sophia Huraka (U Alberta). The work was partially supported by an NSERC Discovery grant.
This Departmental Colloquium is sponsored by the Applied Math seminar group.
When: 3:00 pm (Lubbock's local time is GMT -5) Where: room MATH 011 (basement) ZOOM details:
- Choice #1: use this link Direct Link that embeds meeting and ID and passcode.
- Choice #2: join meeting using this link Join Meeting, then you will have to input the ID and Passcode by hand:
* Meeting ID: 968 6501 7586 * Passcode: Applied
| On computationally efficient methods for testing multivariate distributions with unknown parameters Sara Algeri School of Statistics, University of Minnesota |
| Large cardinals, forcing axioms, and determinacy Nam Trang Department of Mathematics, University of North Texas |
| Dimensional Reduction for the Ferroelectric SmA-Type Phase of Bent-Core Liquid Crystals Tiziana Giorgi Department of Mathematics, University of Alabama |
This Colloquium is sponsored by the TTU Graduate Student Chapter of SIAM.
| The Role of Geometry in Elliptic Boundary Problems Marius Mitrea Department of Mathematics, Baylor University |
What kind of analysis can you do on a given geometric setting? How can you analytically quantify features which are inherently geometric, such as flatness or bending, for a given surface?
| Source Localization Oncological Problem: Recent Results and Open Perspectives Vo Anh Khoa Department of Mathematics, Florida A and M University |
The first theme centers on the development of a new PDE-based inversion, called Variational Quasi-Reversibility Method, designed to tackle the source localization problem in quasilinear form. This approach relies on a special transformation of the inverse problem, resulting in a forward-like problem where various forward solvers can be applied. I will discuss both the weak solvability and strong convergence of the scheme through energy analysis and present some numerical results.
Expanding the source localization model involves incorporating additional design variables. However, in this advanced scenario, certain forward models, including the age-dependent Gompertz model, remain unsolved. In the second theme, I will present a new explicit Fourier-Klibanov method to deal with this forward problem. Stability analysis of the proposed scheme will be reported along with some numerical results.
| Topological Data Analysis and Data Depth for Detecting Anomalies in Weighted Dynamic Networks Asim Dey Department of Mathematical Sciences, University of Texas at El Paso |
This Departmental Candidate Colloquium is at 2:00 PM (UT-6) and may be attended live in ESB1 120, and virtually via this Zoom link.
Meeting ID: 939 5469 1292
Passcode: Dey
| Free probability, Brown measure, and Large-N limit of random matrix models Ping Zhong Department of Mathematics and Statistics, University of Wyoming |
In this talk, I will report some exciting progress on limiting distributions of many deformed random matrix models. We calculated the Brown measures of a large family of random variables in free probability theory, which allows us to investigate many new non-Hermitian random matrix models. Our recent works surpassed all existing results on this topic and unified previous methods. We will discuss their applications to random network, high dimensional statistics, and outliers of large random matrix models.
This Departmental Job Candidate Colloquium may be attended virtually at 2:00 PM (UT-6) via this Zoom link.
| Analyzing Bitcoin Volatility using Double Subordinated Models Abootaleb Shirvani Department of Mathematical Sciences, Kean University |
In this presentation, we delve into the analysis of Bitcoin's volatility using Double Subordinated Models. Our primary focus is on introducing a double subordinated Levy process known as the Normal Double Inverse Gaussian (NDIG) to effectively model the time series properties of the cryptocurrency. Additionally, we present an innovative arbitrage-free option pricing model based on the NDIG process, offering a fresh perspective on the valuation of Bitcoin.
Within the framework of this model, we derive two distinct measures of Bitcoin volatility. The first measure involves combining NDIG option pricing with the Chicago Board Options Exchange VIX model, providing an implied volatility measure that reflects the perspectives of options traders. The second measure delves into implied volatility in the practical world, considering the viewpoints of spot traders and utilizing an intrinsic time formulation.
Both volatility measures are systematically compared to a historical standard deviation-based volatility metric. Notably, with appropriate linear scaling, the NDIG process demonstrates a remarkable capability to accurately capture the observed in-sample volatility of Bitcoin. This presentation aims to contribute valuable insights into comprehending and modeling Bitcoin's volatility dynamics using the powerful framework of Double Subordinated Models.
This Departmental Job Candidate Colloquium is sponsored by the Mathematical Finance seminar group and may be attended virtually at 2:00 PM (UT-6) via this Zoom link.
| Practicality meets Optimality: Real-Time Statistical Inference under Complex Constraints Sen Na Department of Statistics, UC Berkeley |
abstract pdf
This Departmental Job Candidate Colloquium is sponsored by the Statistics seminar group and may be attended virtually at 2:00 PM (UT-6) via this Zoom link.
| Geometric methods with applications to mechanics, fluid-structure interactions, porous media, control, and machine learning Vakhtang Putkaradze Mathematical and Statistical Sciences, University of Alberta |
This Job Candidate Departmental Colloquium is sponsored by the Applied Math seminar group and may be attended in person in ESB1-120 and virtually at 2:00 PM (UT-6) via this Zoom link. This interview will be available in the TTU Mediasite Catalog.
Meeting ID: 947 9013 5459
Passcode: Math