## Past MAMS Seminar Series

### Fall 2023

**November 14, 2023**

**Speaker: **Bartłomiej Zawalski (Kent State University)

**Title: **On star-convex bodies with rotationally invariant sections.

**November 7, 2023**

** Speaker: **Michael Juhos (University of Passau, Germany)

**Limit theorems for mixed-norm sequence spaces with applications to volume distribution II**

**Title:****October 31, 2023**

** Speaker: **Michael Juhos (University of Passau, Germany)

**Limit theorems for mixed-norm sequence spaces with applications to volume distribution**

**Title:****October 17, 2023**

** Speaker: **Michael Roysdon

**Framework for the Theory of Higher Order Convex Bodies III**

**Title:****October 3, 2023**

** Speaker:** Michael Roysdon

**Framework for the Theory of Higher Order Convex Bodies II**

**Title:****September 26, 2023**

** Speaker: **Ulises Fidalgo

**A Riemann-Hilbert problem to study the strong asymptotic behavior of multi-orthogonal polynomials.**

**Title:****September 12, 2023**

** Speaker:** Michael Roysdon

**Framework for the Theory of Higher Order Convex Bodies**

**Title:**

### Spring 2023

**April 4, 2023**

** Speaker: Mengchun Cai
Title: **A central limit theorem for the length of the longest common subsequences for random string.

**March 7, 2023**

** Speaker: Mark Meckes
Title: **Magnitude of metric spaces and intrinsic volumes in normed spaces

### Spring 2022

**January 25, 2022**

**Speaker:** Michael Roysden (Kent State University)

**Title:** Measure theoretic Rogers-Shephard and Zhang inequalities

**February 15, 2022**

**Speaker:** Stanislaw Szarek (CWRU)

**Title:** Löwner-John ellipsoid of a convex body

**February 22, 2022**

**Speaker:** Stanislaw Szarek (CWRU)

**Title:** Löwner-John ellipsoid of a convex body II

**March 1, 2022**

**Speaker:** Dylan Langharst (Kent State)

**Title:** Measure Theoretic Minkowski’s Existence Theorem and Projection Bodies

**March 15, 2022**

**Speaker:** Mathias Sonnleitner (University Graz)

**Title:** Isotropic discrepancy: the gap between order and chaos

**March 22, 2022**

**Speaker:** David Grzybowski (CWRU)

**Title:** A CLT for Traces of Powers of Random Unitary Matrices

**March 29, 2022**

**Speaker:** Mark Meckes (CWRU)

**Title:** MCMC volume estimation and the geometry of high-dimensional convex bodies

**April 5, 2022**

**Speaker:** Elisabeth Werner (CWRU)

**Title:** On the $L_p$ Brunn Minkowski theory

### Fall 2021

**September 29, 2021**

Title: *Best and Random Approximation of a Convex Body by. a Polytope***
Speaker: **Carsten Schuett, University of Kiel

**October 13, 2021**

Title: *Normal Approxiamtion via Markov Processes: Introducing the Stein-Markov Method***
Speaker: **David Grzybowski, Ph.D candidate, CWRU

**October 20, 2021**

Title: *An Analysis and a Probability Result Underlying the M&M Lemma***
Speaker: **Kyle Taljan, Ph.D candidate, CWRU

**October 27, 2021**

Title: *An Analysis and a Probability Result Underlying the M&M Lemma II***
Speaker: **Kyle Taljan, Ph.D candidate, CWRU

**November 10, 2021
**

*Special Analysis & Probability Seminar: Thesis Defense of Kyle Taljan*

Title:

Title:

*Dissertation*

**Kyle Taljan, Ph.D candidate, CWRU**

Speaker:

Speaker:

**November 17, 2021**

Title: *TBA***
Speaker: **Stephanie Egler, Ph.D candidate, CWRU

### Spring 2020

**February 4, 2020**

Title: *Convergence Rates for Determinantal Point Process Induced Random Variables***
Speaker: **Kyle Taljan, Ph.D candidate, CWRU

**February 18, 2020**

Title: *Exact Evaluation of the Triple Integral Products of Wavelet Functions and Application in Inverse Problems***
Speaker: **Julia Dobrosotskaya, Assistant Professor, CWRU

### Fall 2019

**October 1, 2019**

Title: *Sectional Rogers-Shepard Inequalities***
Speaker: **Michael Roysdon (Kent State University)

**October 29, 2019**

Title: *Volume Product and Metric Spaces***
Speaker: **Luis Carlos Garcia (Kent State University)

**November 5, 2019**

Title: *Gravitational Illumination Bodies***
Speaker: **Victor Glasgo, PhD Candidate (CWRU, Department of Mathematics, Applied Mathematics and Statistics)

**November 12, 2019**

Title: *Singularity of 0/1 Random Bernoulli 0/1 Matrices***
Speaker: **Alexander Litvak (University of Alberta, Edmonton)

### Spring 2019

**April 23, 2019
**2:30 p.m.

**Title:**

*On Gruenbaum-Type Inequalities and their Applications*

**Speaker:**Vlad Yaskin, University of Alberta, Edmonton, Canada

**April 16, 2019
**2:30 p.m.

**Title:**

*On the Affine Surface Area*

**Speaker:**Carsten Schütt, University of Kiel

**Tuesday March 5, 2019
**2:30 p.m.

**Title:**

*Big Data and Floating Body*

**Speaker:**Carsten Schütt, University of Kiel

**Tuesday February 26, 2019
**2:30 p.m.

**Title:**

*Fractional Sobolev Norms and BV Functions on Manifolds*

**Speaker:**Andreas Kreuml, Vienna Technical Institute

**Tuesday February 19, 2019
**2:30 p.m.

**Title:**

*Spherical Centroid Bodies*

**Speaker:**Florian Besau, Vienna Technical Institute

**Tuesday February 12, 2019
**2:30 p.m.

**Title:**

*Estimates for the Eigenvalues of the Sinc-Kernel Operator*

**Speaker:**Kyle Taljan, MAMS PhD Candidate

**Tuesday February 5, 2019
**2:30 p.m.

**Title:**

*Estimates for the Eigenvalues of the Sinc-Kernel Operator*

**Speaker:**Kyle Taljan, MAMS PhD Candidate

### Fall 2018

**Tuesday December 4, 2018
**2:30 p.m.

**Title:**

*The Hausdorff Dimension*

**Speaker:**Runtian Miao, Graduate Student, Department of Mathematics, Applied Mathematics, and Statistics

**Tuesday November 20, 2018
**2:30 p.m.

**Title:**

*Tensor Products of Normed Spaces*

**Speaker:**Stanislaw Szarek, Kerr Professor of Mathematics, CWRU Department of Mathematics, Applied Mathematics, and Statistics

**Tuesday November 13, 2018
**2:30 p.m.

**Title:**

*Truncations of Haar Distributed Random Matrices*

**Speaker:**Kathryn Stewart, PhD Candidate, Department of Mathematics, Applied Mathematics, and Statistics

**Tuesday October 16, 2018
**2:30 p.m.

**Title:**

*Multiscale Conservation Laws Driven by L/’evy Stable and Linnik Diffusions: Asomptotics, Explicit Representations, Shock Creation, Preservation, and Dissolution*

**Speaker:**Wojbor Woyczynski, Professor, CWRU Department of Mathematics, Applied Mathematics, and Statistics

**Tuesday October 9, 2018
**2:30 p.m.

**Title:**

*A Quenched Central Limit Theorem in a Corner Growth Setting*

**Speaker:**Mark Meckes, Professor, CWRU Department of Mathematics, Applied Mathematics, and Statistics

**Tuesday September 18, 2018
**2:30 p.m.

**Title:**

*Sobolev Martingales*

**Speaker:**Michal Wojciechowski, Polish Academy of Sciences, Warsaw

### Spring 2018

**Tuesday April 24, 2018
**3:00 p.m.

Title:

*Geometry and Martingales in Banach Spaces*

Speaker: Wojbor Woyczynski, Case Western Reserve University

**Tuesday April 17, 2018
**3:00 p.m.

Title:

*Wulff Shapes and Characterization of Simplies via a Bezout Type Inequality*

Speaker: Christos Saraoglu, Kent State University

**Tuesday April 10, 2018
**3:00 p.m.

Title:

*Improving Statistical Decision Procedures*

Speaker: Manfred Danker, Pennsylvania State University

**Tuesday March 20, 2018
**3:00 p.m.

Title:

*Empty Simplices*

Speaker: Matthias Reitzner, University of Osnabrueck

**Tuesday March 6, 2018
**3:00 p.m.

Title:

*Generalizations of Gruenbaum’s Inqequality*

Speaker: Ning Zhang, Kent State University

**Tuesday February 20, 2018
**3:00 p.m.

Title:

*An upper bound on the smallest singular value of a square random matrix*

Speaker: Kateryna Tatarko, University of Edmonton

**Tuesday February 13, 2018**

3:00 p.m.

Title: *Duality of Floating and Illumination Bodies*

Speaker: Olaf Mordhorst, Vienna Technical University

**Tuesday February 6, 2018**

3:00 p.m.

Title: *Type and Cotype of Banach spaces*

Speaker: Carsten Schuett, University of Kiel

### Fall 2017

**Monday, September 11, 2017**

3:45 p.m.

Title: Introduction to concentration inequalities, I

Speaker: Mark Meckes (Associate Professor, Case Western Reserve University)

**Monday, September 18, 2017**

3:45 p.m.

Title: Introduction to concentration inequalities, II

Speaker: Mark Meckes (Associate Professor, Case Western Reserve University)

**Monday, September 25, 2017**

3:45 p.m.

Title: Introduction to concentration inequalities, III

Speaker: Mark Meckes (Associate Professor, Case Western Reserve University)

**Monday, October 2, 2017**

3:45 p.m.

Title: Introduction to concentration inequalities, IV

Speaker: Mark Meckes (Associate Professor, Case Western Reserve University)

**Monday, October 9, 2017**

3:45 p.m.

Title: Introduction to concentration inequalities, V

Speaker: Mark Meckes (Associate Professor, Case Western Reserve University)

**Monday, October 30, 2017**

3:45 p.m.

Title: Introduction to concentration inequalities, VI

Speaker: Mark Meckes (Associate Professor, Case Western Reserve University)

**Monday, November 6, 2017**

3:45 p.m.

Title: Introduction to concentration inequalities, VII

Speaker: Mark Meckes (Associate Professor, Case Western Reserve University)

**Monday, November 13, 2017**

3:45 p.m.

Title: Truncations of Random Unitary Matrices

Speaker: Kathryn Lockwood (PhD Student, Case Western Reserve University)

**Spring 2017**

**Tuesday, January 24, 2017**

3:00 p.m.

Title: From longest increasing subsequences to random surfaces

Speaker: Leonid Petrov (Assistant Professor, University of Virginia)

**Tuesday, February 21, 2017**

3:00 p.m.

Title: Dual curvature measures and the dual Minkowski problem

Speaker: Yiming Zhao (Adjunct Instructor, New York University)

**Tuesday, March 7, 2017**

3:00 p.m.

Title: The affine surface area in Euclidean convex geometry and beyond

Speaker: Florian Besau (Postdoctoral Researcher, Goethe University Frankfurt)

**Tuesday, March 28, 2017**

3:00 p.m.

Title: Remarks on the (B) conjecture

Speaker: Liran Rotem (Dunham Jackson Assistant Professor, University of Minnesota)

**Tuesday, April 4, 2017**

3:00 p.m.

Title: Reconstructing polytopes from projections or sections

Speaker: Sergii Myroshnychenko (Graduate Student, Kent State University)

**Tuesday, April 11, 2017**

3:00 p.m.

Title: Random polytopes: An introduction and recent developments

Speaker: Julian Grote (PhD Student, University of Bochum and Case Western Reserve University)

**Tuesday, May 2, 2017**

3:00 p.m.

Title: Random polytopes: An introduction and recent developments-Part II

Speaker: Julian Grote (PhD Student, University of Bochum and Case Western Reserve University)

### Fall 2016

**Tuesday, September 20, 2016**

3:00 p.m.

Title: Can one achieve truly quantum correlations with PPT states?

Speaker: Ben Li (PhD Student, Case Western Reserve University)

**Tuesday, September 27, 2016**

3:00 p.m.

Title: Occupation times of discrete-time fractional Brownian motion

Speaker: Manfred Denker (Professor, Penn State University)

**Tuesday, October 4, 2016**

3:00 p.m.

Title: Can one achieve truly quantum correlations with PPT states? (Part II)

Speaker: Ben Li (PhD Student, Case Western Reserve University)

**Tuesday, October 18, 2016**

3:00 p.m.

Title: Can one achieve truly quantum correlations with PPT states? (Part III)

Speaker: Ben Li (PhD Student, Case Western Reserve University)

**Tuesday, November 1, 2016**

3:00 p.m.

Title: The entropy power inequality for the Renyi entropy

Speaker: Arnaud Marsiglietti (Postdoctoral Research Associate in Mathematics, California Institute of Technology)

**Tuesday, November 15, 2016**

3:00 p.m.

Title: Self-similarity in the eigenvalues of random unitary matrices

Speaker: Mark Meckes (Associate Professor, Case Western Reserve University)

**Tuesday, November 29, 2016**

3:00 p.m.

Title: Self-similarity in the eigenvalues of random unitary matrices (Part 2)

Speaker: Mark Meckes (Associate Professor, Case Western Reserve University)

### Spring 2016

**Tuesday, January 26, 2016**

3:00 p.m.

Title: Maximizing diversity in biology and beyond (Part 1)

Speaker: Mark Meckes (Associate Professor, Case Western Reserve University)

**Tuesday, February 2, 2016**

3:00 p.m.

Title: Affine invariant points

Speaker: Olaf Mordhorst (PhD Student, University of Kiel)

**Tuesday, February 9, 2016**

3:00 p.m.

Title: Maximizing diversity in biology and beyond (Part 2)

Speaker: Mark Meckes (Associate Professor, Case Western Reserve University)

**Tuesday, February 16, 2016**

3:00 p.m.

Title: A simple proof of Størmer’s theorem

Speaker: Stanislaw Szarek (Kerr Professor of Mathematics, Case Western Reserve University)

**Tuesday, March 22, 2016**

3:00 p.m.

Title: The Surface Area Deviation of the Euclidean Ball and a Polytope

Speaker: Steven Hoehner (PhD Student, Case Western Reserve University)

**Tuesday, March 29, 2016**

3:00 p.m.

Title: The Size of Convex Hulls in Hilbert Spaces

Speaker: Werner Linde (Visiting Professor, University of Delaware)

**Tuesday, April 5, 2016**

3:00 p.m.

Title: Fractional Pearson Diffusion

Speaker: Nikolai N. Leonenko (Professor, Cardiff University)

**Tuesday, April 19, 2016**

3:00 p.m.

Title: Randomized isoperimetric inequalities

Speaker: Peter Pivovarov (Assistant Professor, University of Missouri)

### Fall 2015

**Tuesday, September 15, 2015**

3:00 p.m.

Title: On the approximation of a polytope by its dual L_p-centroid bodies

Speaker: Elisabeth Werner (Professor, Case Western Reserve University)

**Tuesday, September 29, 2015**

3:00 p.m.

Title: New invariant projections on the Hardy space on the polydisc

Speaker: Maciej Rzeszut (Polish Academy of Sciences)

**Tuesday, October 6, 2015**

3:00 p.m.

Title: K-convexity (Part I)

Speaker: Stanislaw Szarek (Professor, Case Western Reserve University)

**Tuesday, October 13, 2015**

3:00 p.m.

Title: K-convexity (Part II)

Speaker: Stanislaw Szarek (Professor, Case Western Reserve University)

**Tuesday, October 27, 2015**

3:00 p.m.

Title: The Floating Body in Real Space Forms

Speaker: Florian Besau (Lecturer, Case Western Reserve University)

**Tuesday, November 3, 2015**

3:00 p.m.

Title: Multiscale conservation laws driven by Lévy stable and Linnik diffusions: asymptotics, explicit representations, shock creation, preservation and dissolution

Speaker: Wojbor Woyczynski (Professor, Case Western Reserve University)

**Tuesday, November 10, 2015**

3:00 p.m.

Title: Banach-Mazur distance to centrally symmetric convex bodies after Gordon, Litvak, Meyer and Pajor

Speaker: Olaf Mordhorst (PhD Student, Christian-Albrechts-Universität zu Kiel, Research Scholar, Case Western Reserve University)

**Thursday, November 12, 2015**

3:00 p.m. *in* *Yost 335*

Title: Stability of some geometric inequalities and their application to the rate of convergence of Steiner, Minkowski and Blaschke symmetrization

Speaker: Alex Segal (Tel Aviv University)

**Tuesday, November 17, 2015**

3:00 p.m.

Title: Approximation of the Entries of a Random Orthogonal Matrix by Independent Standard Normals

Speaker: Kathryn Lockwood (PhD Student in Mathematics, Case Western Reserve University)

### Spring 2015

**Friday, February 6, 2015**

12:45 – 1:45 p.m.

Title: Typical marginals of convex bodies

Speaker: Mark Meckes (Case Western Reserve University)

**Friday, February 20, 2015**

12:45 – 1:45 p.m. with refreshments at 12:30 p.m.

Title: Matrix Inequalities and Applications

Speaker: Ben Li (Case Western Reserve University)

**Friday, March 6, 2015**

12:45 – 1:45 p.m.

Title: Matrix Inequalities and Applications II

Speaker: Ben Li (Case Western Reserve University)

**Friday, March 20, 2015**

12:45-1:45 p.m. in Yost 335

Title: Markov Processes With Linear Regressions and Quadratic Conditional Variances

Speaker: Wlodzimierz Bryc (University of Cincinnati)

**Friday, April 10, 2015**

1:00-2:00 p.m. in Yost 306

Title: Banded Matrices and Fast Inverses

Speaker: Gilbert Strang (MIT)

**Friday, April 24, 2015**

12:45-1:45 p.m. in Yost 335

Title: “Concentration of the Spectral Measure of a Random Matrix Ensemble”

Speaker: David Buzinski (Undergraduate Student, Case Western Reserve University)

**Thursday, May 7, 2015**

12:45-1:45 p.m. in Yost 335

Title: On the Perimeter of a Convex Set

Speaker: Galyna Livshyts (Ph.D. Student, Kent State University)

### Spring 2024

**4/17/2024**

**Speaker**: Dr. Michael Kuian

**Title**: Solution of Linear Ill-Posed Problems by Modified Truncated Singular Value Expansion

**Abstract**: The numerical solution of linear ill-posed problems generally requires incorporation of regularization to yield a meaningful approximate solution. A common approach to compute a regularized approximate solution is to apply the truncated singular value expansion of the operator. A modification of the truncated singular value expansion for linear discrete ill-posed problems in finite dimensions was shown to furnish approximate solutions of higher quality than the standard truncated singular value expansion. This work extends the modified singular value expansion to ill-posed problems in a Hilbert space setting.

**4/10/2024**

**Speaker**: Dr. David Gurarie

**Title**: Modeling atmospheric chemistry-mixing via moment closure scheme

**Abstract**: Multiple chemical species are released into atmosphere from the earth surface and aloft, where they undergo turbulent mixing and a chain of reactions. Some of them (ozone, nitric oxides) are major air pollutants, subject to air quality control. To understand and predict mixing-chemistry dynamics different modeling approaches are utilized, ranging from simple ‘box chemistry’ (well-mixed concentrations) to large turbulent mixing schemes based on large-eddy simulations (LES). The former allow detailed chemical makeup and processes, but grossly undercount mixing contribution. The latter resolve fine detail of turbulent mixing but have limited scope due to high power computing resources and expertise required to run them.

We developed an intermediate level model that employs moment closure scheme for turbulent mixing coupled to chemistry. It requires minimal resources (desktop), and its predictions are comparable to LES.

The talk will give a general introduction to atmospheric chemistry-mixing. Then I will outline a moment closure scheme (called SOMCRUS), developed with collaborators at NCAR (Boulder, CO). I will elaborate its mathematical setup and computer implementation. Model simulations will be compared to LES case studies, and further applications and development discussed.

**4/3/2024**

**Speaker**: Dr. Abdul-Nasah Soale

**Title**: Regression graphics for regression with metric-valued response objects

**Abstract**: As novel data collection becomes increasingly common, traditional dimension reduction and data visualization techniques are becoming inadequate to handle these complex data. A surrogate-assisted sufficient dimension reduction (SDR) method for regression with a general metric-valued response on Euclidean predictors is proposed. The response objects are mapped to a real-valued distance matrix using an appropriate metric and then projected onto a large sample of random unit vectors to obtain scalar-valued surrogate responses. An ensemble estimate of the subspaces for the regression of the surrogate responses versus the predictor is used to estimate the original central space. Under this framework, classical SDR methods such as ordinary least squares and sliced inverse regression are extended. The surrogate-assisted method applies to responses on compact metric spaces such as Euclidean, distributional, functional, and other response types. An extensive simulation experiment demonstrates the superior performance of the proposed surrogate-assisted method on synthetic data compared to existing competing methods where applicable. The analysis of the distributions of county level COVID-19 transmission rates in the United States as a function of demographic characteristics is also provided. The theoretical justifications are included as well.

**3/6/2024**

**Speaker**: Dr. Weihong Guo

**Title**: Nonnegative and Nonlocal Sparse Tensor Factorization Based Hyperspectral Image Super-Resolution

**Abstract**: Hyperspectral image (HSI) super-resolution refers to enhancing the spatial resolution of a 3-D image with many spectral bands (slices). It is a seriously ill-posed problem when the low-resolution (LR) HSI is the only input. It is better solved by fusing the LR HSI with a high-resolution (HR) multispectral image (MSI) for a 3-D image with both high spectral and spatial resolution. In this talk, we propose a novel nonnegative and nonlocal 4-D tensor dictionary learning-based HSI super-resolution model using group-block sparsity. By grouping similar 3-D image cubes into clusters and then conduct super-resolution cluster by cluster using 4-D tensor structure, we not only preserve the structure but also achieve sparsity within the cluster due to the collection of similar cubes. We use 4-D tensor Tucker decomposition and impose nonnegative constraints on the dictionaries and group-block sparsity. Numerous experiments demonstrate that the proposed model outperforms many state-of-the-art HSI super-resolution methods.

**1/31/2024**

**Speaker**: Dr. Anuj Abhishek

**Title**: An operator learning framework for an inverse problem in Electrical Impedance Tomography

**Abstract**: Neural network architectures such as Fourier Neural Operators (FNO) and Deep Operator Networks (Deep-O-Net) have been shown to be fairly useful in approximating an operator between two function spaces. In this talk, we will briefly review an inverse problem that arises in Electrical Impedance tomography as well as review such operator learning network architectures. We will then see how we might use similar network architectures to learn (or, approximate) a map that takes in as its input the Dirichlet to Neumann operator and outputs the corresponding conductivity function. This is based on an unfinished ongoing work with my collaborator, Thilo Strauss (Xi’an Jiaotong-Liverpool University).

### Fall 2023

**11/29/2023**

**Speaker**: Dr. Sakshi Arya

**Title**: Kernel Epsilon-Greedy Approach for Contextual Bandits

**Abstract**: Contextual bandit algorithms are popular for sequential decision-making in several practical applications, ranging from online advertisement recommendations to mobile health. The goal of such problems is to maximize cumulative reward over time for a set of choices/arms while considering covariate (or contextual) information. Epsilon-greedy is a popular heuristic for the multi-armed bandit problem, however, it is not one of the most studied algorithms theoretically in the presence of contextual information. The epsilon-greedy strategy is studied in nonparametric bandits, i.e. when no parametric form is assumed for the reward functions. The similarities between the covariates and expected rewards are assumed to be modelled as arbitrary linear functions of the contexts’ images in a specific reproducing kernel Hilbert space (RKHS). A kernel epsilon-greedy algorithm is proposed and its convergence rates are established for estimation and cumulative regret, which are closely tied to the intrinsic dimensionality of the RKHS. The rates closely match the optimal rates for linear contextual bandits when restricted to a finite-dimensional RKHS. We then compare the results with existing algorithms like kernel Upper Confidence Bounds (UCB) on synthetic data.

**10/11/2023**

**Speaker**: Dr. Daniela Calvetti

**Title**: Group sparsity promotion via Bayesian hierarchical models in dictionary learning/coding

**Abstract**: Dictionary learning/coding continues to gain popularity in several applications where there is a wealth of experimental and synthetic data. In contexts where it is believed that only a few dictionary items play a role in the task of interest, sparsity promoting algorithms are particularly attractive. In this talk some novel ideas for sprasity and group sparsity promotion to reduce the computational costs and improve the performance of dictionary-based procedures will be discussed. An application to hyperspectral imaging will be presented.

**9/20/2023**

**Speaker**: Professor Erkki Somersalo

**Title**: Computationally efficient sampling methods for sparsity promoting hierarchical Bayesian models

**Abstract**: Bayesian hierarchical models have been demonstrated to provide efficient algorithms for finding sparse solutions to ill-posed inverse problems. The models comprise typically a conditionally Gaussian prior model for the unknown, augmented by a hyperprior model for the variances. A widely used choice for the hyperprior is a member of the family of generalized gamma distributions. Most of the work in the literature has concentrated on numerical approximation of the maximum a posteriori (MAP) estimates, and less attention has been paid on sampling methods or other means for uncertainty quantification. Sampling from the hierarchical models is challenging mainly for two reasons: The hierarchical models are typically high-dimensional, thus suffering from the curse of dimensionality, and the strong correlation between the unknown of interest and its variance can make sampling rather inefficient. This work addresses mainly the first one of these obstacles. By using a novel reparametrization, it is shown how the posterior distribution can be transformed into one dominated by a Gaussian white noise, allowing sampling by using the preconditioned Crank-Nicholson (pCN) scheme that has been shown to be efficient for sampling from distributions dominated by a Gaussian component. Furthermore, a novel idea for speeding up the pCN in a special case is developed, and the question of how strongly the hierarchical models are concentrated on sparse solutions is addressed in light of a computed example.

The work is in collaboration with Professor Daniela Calvetti.

**9/13/2023**

**Speaker**: **Dr. **Jenny Brynjarsdottir

**Title**: Polya-Gamma data augmentation schemes for posterior sampling – and my unexpected NIH adventure

**Abstract**: We develop a double Pólya-Gamma data augmentation scheme for posterior sampling from a Bayesian hierarchical model of total and categorical count data. The scheme applies to a Negative Binomial – Binomial (NBB) hierarchical regression model with logit links and normal priors on regression coefficients. The approach is shown to be very efficient and in most cases out-performs the Stan program. We apply the hierarchical modeling framework and the Póya-Gamma data augmentation scheme to human mitochondrial DNA data.

**9/13/2023**

**Speaker**: **Dr. **Jenny Brynjarsdottir

**Title**: Polya-Gamma data augmentation schemes for posterior sampling – and my unexpected NIH adventure

**Abstract**: We develop a double Pólya-Gamma data augmentation scheme for posterior sampling from a Bayesian hierarchical model of total and categorical count data. The scheme applies to a Negative Binomial – Binomial (NBB) hierarchical regression model with logit links and normal priors on regression coefficients. The approach is shown to be very efficient and in most cases out-performs the Stan program. We apply the hierarchical modeling framework and the Póya-Gamma data augmentation scheme to human mitochondrial DNA data.

### Spring 2023

**4/12/2023**

**Speaker: Dr. Wanda Strychalski
**

**I will provide a brief overview of several numerical methods for simulating deformable elastic structures immersed in viscous fluid. I will then explain the idea behind the method of regularized Stokeslets, a fast and straightforward approach for simulating 2D models of cells interacting with their environment, at an introductory level.**

**Title:**Numerical Methods for Simulating Fluid-Structure Interaction Problems in Biology**Abstract:****4/5/2023**

** Speaker: Dr. Ulises Fidalgo
Title: A multi-orthogonal polynomials’ approach to a bulk queueing model
Abstract: **We consider a stationary Markov process that models certain queues with a bulk service of a fixed number $m$ of admitted customers. We find an integral expression of its transition probability function in terms of certain multi-orthogonal polynomials with respect to a system of distributions that contain measures supported on starlike subsets of the complex plane. We give explicit expressions for such polynomials and distributions in terms of the solution of an algebraic equation. We also verify that all the states can be reached from each other.

**3/8/2023**

**Speaker: Xiaofeng Wang, PhD Department of Quantitative Health Sciences **

** Lerner Research Institute **

** Cleveland Clinic
Title: Adaptive Density Peak Clustering for Complex Data
Abstract: **Common limitations of existing clustering methods include slow algorithm convergence, instability of the pre-specification on intrinsic parameters, and the lack of robustness to outliers. In this talk, we present a novel clustering method using an adaptive density peak detection technique. It is a quick cluster center identification algorithm based on the two

measures of each data observation: the density estimate and the distance to the closest observation with a higher functional density. Our clustering method is computationally fast since it does not need an iterative process. We apply our approach to mixed data with both categorical and continuous variables, as well as complex multivariate functional data. The flexibility and advantages of the method are examined by comparing it with other existing clustering methods in simulation studies. Two user-friendly R packages, ADPclust and FADPclust, have been developed for public use. Finally, the new clustering method is applied to a real case study in lung cancer research.

**3/1/2023**

** Speaker: Anirban Mondal
Title: Bayesian Uncertainty Quantification of Local Volatility Model using Option Price Data
Abstract: **Local volatility is an important quantity in option pricing, portfolio hedging, and risk management. It is not directly observable from the market; hence calibrations of local volatility models are necessary using observable market data. Unlike most existing point-estimate methods, we cast the large-scale nonlinear inverse problem into the Bayesian framework, yielding a posterior distribution of the local volatility, which naturally quantifies its uncertainty. This extra uncertainty information enables traders and risk managers to make better decisions. To alleviate the computational cost, we apply Karhunen–L\`oeve expansion to reduce the dimensionality of the Gaussian Process prior for local volatility. A modified two-stage adaptive Metropolis algorithm is used to sample the posterior probability distribution, which further reduces computational burdens caused by repetitive numerical forward option pricing model solver and time of heuristic tuning. We demonstrate our methodology with both synthetic and market data.

**2/15/2023**

** Speaker: Jiasen Zhang, CWRU PhD student
Title: A New Regularization for Deep Learning-Based Segmentation of Images with Fine Structures and Low Contrast
Abstract: **Deep learning methods have achieved outstanding results in many image processing and computer vision tasks, such as image segmentation. However, they usually do not consider spatial dependencies among pixels/voxels in the image. To obtain better results, some methods have been proposed to apply classic spatial regularization, such as total variation, into deep learning models. However, for some challenging images, especially those with fine structures and low contrast, classical regularizations are not suitable. We derived a new regularization to improve the connectivity of segmentation results and make it applicable to deep learning. Our experimental results show that for both deep learning methods and unsupervised methods, the proposed method can improve performance by increasing connectivity and dealing with low contrast and, therefore, enhance segmentation results.

**2/8/2023**

**Title:** Estimating Non-stationary Spatial Covariance Matrix using Multi-resolution Knots

** Speaker: Siddhartha Nandy
Abstract: **Providing a best linear unbiased predictor (BLUP) has certain challenges for spatial data in high-dimensional setup. The process of estimation as well as prediction involves inverting an n × n covariance matrix, which consumes time up to an order of n3. Studies have showed that, the potential observed process covariance matrix can be decomposed into two additive matrix components, one from measurement error, and another from a non-stationary (NS) process. The NS component is often assumed to be fixed but low rank. This structure allows us to write the NS process as a linear combination of fixed numbers of spatial random effects, by truncating the Karhunen and Loe ́ve expansion. This technique is known as fixed rank kriging (FRK), and this improves the computation time up to an order of nr2, where r is rank of the low rank covariance matrix. In this work we rewrite the un-derlying spatial process as a linear combination of Kn(∼ n > r) random effects, although only a few among these are responsible to quantify the covariance structure. Furthermore we decompose the covariance matrix of the random effect to a Kn × Kn cholesky decom-position. We then consider a two step approach by using a group-wise penalized likelihood, where each row of the lower triangular component is penalized, and then estimate the over-all covariance based on the initial estimate. We present and exploit the connection between the sparsity of each row and column to that of eigen values of the cholesky matrix. We validate our findings over simulation study and by applying to a spring seasonal temperature data on Colorado, US obtained from the fields package in R.

**2/1/2023**

**Title: Stochastic Sampling of Skeletal Muscle Forces During Human Movement**

**Speaker: Mercy Amankwah, MAMS PhD student**

**Abstract: **Movement in the human body is made possible by a coordinated joint effort from several skeletal muscles. The muscles contract and relax around joints to generate forces which contribute to the load at the joints. A very simple task performed by an individual such as raising an arm or lifting a leg can be accomplished with a wide range of muscle forces due to the concept of muscle redundancy. These muscle forces are not easily obtainable. We formulate a problem that has the muscle forces as unknowns. In this presentation, we will discuss how we obtain feasible estimates for the forces generated by these muscles at the various joints. In addition, we transform the problem to be solved into the Bayesian framework and while using Markov Chain Monte Carlo methods to produce feasible sample solutions, we quantify the uncertainties in these solution samples. Furthermore, inspired by the principles surrounding the Feynman-Kac formula, we propose an approach that smoothly connects the muscle activation pattern at each time instance to mimic the smoothness exhibited in normal human movement.

### FALL 2022

**12/7/2022**

**Title: Hierarchical solution of sparse dictionary reconstruction with clustered entries**

**Speaker: ****Alberto Bocchinfuso**

**Abstract: **Dictionary learning algorithms seek to explain observed data in terms of few atoms in a precomputed dictionary of possible outcomes. The algorithms can be used for clustering and classification, or to interpret data in problems where model-based methods may be computationally infeasible.

If the dictionary entries are similar to each other, the problem of identifying an approximation may become ambiguous. A possible solution is to break the process into two steps.

We begin by reducing the dictionary by clustering the atoms and approximating each cluster by a few feature vectors. The first task is to identify clusters that contribute to the representation of the data. This reduced dictionary learning problem can be solved using sparse coding when the data admit sparse representation. Ideally, only a few clusters are sufficient to explain the data.

The second step is to represent data in terms of a subset of the original dictionary, excluding atoms corresponding to clusters not selected in the first step. This process reduces ambiguities, and lowers the overall computational complexity sparse coding can be used to identify the best explaining atoms.

**11/9/2022**

**Title: A PDE-Based Analysis of the Symmetric Two-Armed Bernoulli Bandit**

**Speaker: Vladimir Kobzar (Columbia university) **

**Abstract:** The multi-armed bandit is a classic sequential prediction problem. At each round, the predictor (player) selects a probability distribution from a finite collection of distributions (arms) with the goal of minimizing the difference (regret) between the player’s rewards sampled from the selected arms and the rewards of the arm with the highest expected reward. The player’s choice of the arm and the reward sampled from that arm are revealed to the player, and this prediction process is repeated until the final round. Our work addresses a version of the two-armed bandit problem where the arms are distributed independently according to Bernoulli distributions and the sum of the means of the arms is one (the symmetric two-armed Bernoulli bandit). In a regime where the gap between these means goes to zero and the number of prediction periods approaches infinity, we obtain the leading order terms of the expected regret and pseudoregret for this problem by associating each of them with a solution of a linear parabolic partial differential equation. Our results improve upon the previously known results; specifically we explicitly compute the leading order term of the optimal regret and pseudoregret in three different scaling regimes for the gap. Additionally, we obtain new non-asymptotic bounds for any given time horizon. This is joint work with Robert Kohn available at https://arxiv.org/abs/2202.__05767.__

**10/19/22**

** Title: **Patterns, algorithms and your friends

**Speaker**: Dr. Emily Evans, Department of Mathematics, Brigham Young University

**Abstract:**In this talk, I will give a survey of methods used to determine resistance distance in networks. These techniques will range from linear algebra to geometric simplices and from numerical optimization to projection methods. For each method discussed an illustrative example of the technique will be provided. This talk will also feature interesting numerical patterns and real-world applications. Finally, I will close my talk with a number of conjectures related to resistance distance.

**10/5/22**

**Title:**Crowdsourced Ionospheric Observations: Data and Discussion

**Speaker Name/Affiliation:**Kristina Collins, PhD Candidate, Electrical Engineering, CWRU

**Abstract:**Understanding ionospheric variability remains a frontier topic in the space physics community. This variability is key not only to understanding ionospheric dynamics in its own right, but also as a means to understanding the coupled geospace system as a whole, which includes the ionosphere’s connection to both space above and the neutral atmosphere below. Sources of variability from space include solar flares that last minutes, substorms that last a few hours, and ionospheric and geomagnetic storms that can last days. Sources of variability from below include traveling ionospheric disturbances (TIDs) associated with atmospheric gravity waves (AGWs), which may be caused by tornadoes, tsunamis, or high latitude sources.

__ohx.2022.e00289) are presented for a period of time spanning late 2019 to early 2022 (www.doi.org/10.5281/zenodo.__

__6622111). Software tools for the visualization and analysis of this living dataset are provided (https://github.com/HamSCI/__

__hamsci_psws) and exemplars of short- and long-term variability and events will be presented and discussed.__

This presentation will be followed by an

__open discussion__of what applied mathematical methods may be used to leverage this dataset.

9/21/22

9/21/22

**Title:**Hypermodels, Sparsity and Approximate Bayesian Computing

**Speaker:**Dr. Erkki Somersalo, CWRU

**Abstract:** In numerous applications involving an underdetermined large scale inverse problem, sparsity of the solution is a desired property. In the Bayesian framework of inverse problems, sparsity requirement of the solution may be implemented by properly defining the prior distribution. While Gaussian priors are not well suited for promoting sparsity, certain hierarchical, conditionally Gaussian models have been demonstrated to be efficient. In this talk, we review a general class of conditionally Gaussian hypermodels that provide a flexible framework for promoting sparsity of the solution, and discuss approximate iterative methods that can be used both for finding single sparse solutions as well as for approximate sampling of the posterior distributions. The motivation for this work comes from an ongoing work on brain imaging using magnetoencephalography data.

### Spring 2022

**January 31, February 7, February 14: Dr. Erkki Somersalo (CWRU)**

Title: Monte Carlo integration: Ideas and insights

Abstract: Monte Carlo integration represents one of the bread-and-butter methods in Bayesian computing, and it continues to be a challenge in particular in high dimensional inverse problems, e.g., when the quantity of interest is a discretized version of a distributed parameter.

This lecture contains a gentle introduction in the topic, and reviews some of the methods that have recently gained popularity, such as the preconditioned Crank-Nicholson (pCN) algorithm.

**February 21, Dr. Anirban Mondal (CWRU)**

Abstract: The talk will first focus on two quite powerful ideas in the Markov chain Monte Carlo literature — the two-stage Metropolis-Hastings sampler (a.k.a. delayed acceptance Metropolis-Hastings sampler) and the adaptive Metropolis sampler. I will discuss how these algorithms are very useful for high-dimensional posterior sampling in the Bayesian inverse problem setting. In particular, the former addresses the computational issues for repeated evaluation of expensive likelihoods, the latter addresses the step size tuning and related convergence issues for high-dimensional target densities. Then I will introduce a new sampling algorithm – a two-stage adaptive Metropolis algorithm – where we combine the ideas of these two useful samplers. Being a combination of the two, this new sampler is superior to both predecessors in terms of computational efficiency. The proposals of the sampler are dependent on all the previous states so the chain loses its Markov property, but we prove that it retains the desired ergodicity property

**February 28, Dr. Jenny Brynjarsdottir (CWRU)**

Title: Optimal Estimation Versus MCMC for CO2 Retrievals

Abstract: The Orbiting Carbon Observatory-2 (OCO-2) collects infrared spectra from which atmospheric properties are retrieved. OCO-2 operational data processing uses optimal estimation (OE), a state-of-the-art approach to inference of atmospheric properties from satellite measurements. One of the main advantages of the OE approach is computational efficiency, but it only characterizes the first two moments of the posterior distribution of interest. Here we obtain samples from the posterior using a Markov Chain Monte Carlo (MCMC) algorithm and compare this empirical estimate of the true posterior to the OE results. We focus on 600 simulated soundings that represent the variability of physical conditions encountered by OCO-2 between November 2014 and January 2016.

**March 14, Dr. Mark Meckes (CWRU)**

**March 21 Dr. Daniela Calvetti (CWRU)**

*See COVID-19 Forecasts for 31 Northern Ohio Counties.*

**March 28 Dr. David Gurarie (CWRU)**

Title: Quantifying diagnostic uncertainty for Schistosomiasis with implications to its control and elimination

Abstract: Schistosomiasis is one of neglected tropical diseases caused by parasitic worm Schistosome, circulating between human and snail hosts. The disease is widely spread in many tropical and subtropical countries. It is targeted for control and elimination by WHO, and the proposed strategies rely on its monitoring/evaluation at local community level, using available diagnostic tools. The latter proved notoriously difficult due to extreme variability of diagnostic (test) outcomes. To quantify diagnostic variability and explore its implications for control, we utilized an extensive dataset of large-scale control surveillance studies conducted in 3 African countries (SCORE project).

By combining statistical analysis, mathematical models and computer tools, we discovered new patterns and disease markers relevant to schistosomiasis. Furthermore, we develop consistent procedures and computer tools for diagnostic resampling of test data, applicable to any community (outside SCORE countries). The new resampling methodology has many applications. Here we shall focus on dynamic models of Schistosome transmission calibrated with the SCORE data, and its application to WHO control strategies.

The talk will elaborate data-driven pattern discovery, and dynamic modeling of schistosomiasis.

**April 4, Dr. Weihong Guo (CWRU)**

### Spring 2020

**February 26, 2020**

Title: *Measuring Velocity in Turbulent Flows: Moving Beyond Particle Image Velocimetry***
Speaker: **Bryan Schmidt, MAE, CWRU

### Fall 2019

**October 23, 2019**

Title: *Two Approaches to Phase Reduction for Stochastic Oscillators***
Speaker: **Peter Thomas, Professor (CWRU, Department of Mathematics, Applied Mathematics and Statistics)

**October 30, 2019**

Title: *Bayesian Hierarchical Models: Sparsity, Convexity and Models Reduction*

**Speaker: **Daniela Calvetti, Professor (CWRU, Department of Mathematics, Applied Mathematics and Statistics)

** November 13, 2019
Title: **Can we Eliminate Schistosomiasis? Insights from Mathematical Modeling, Data Analysis and Computation

**David Gurarie, Professor (CWRU, Department of Mathematics, Applied Mathematics and Statistics)**

Speaker:

Speaker:

### Spring 2019

**Monday April 29, 2019****
**4:00 p.m.

**Title:**Shape Versus Timing: Linear Responses of a Limit Cycle with H

*ard Boundaries Under Perturbation*

Yangyang Wang, Mathematical Biosciences Institute

**Speaker:****April 22, 2019
**4:00 p.m.

**Title:**

*Characterizing Diffusion in Porous and Crowded Environments with Correlation-Based Super Resolution Imaging*

**Speaker:**Lydia Kisley, Department of Physics, Case Western Reserve University

**Monday April 15, 2019****
**4:00 p.m.

**Title:**Integral Deferred Correction Methods for Multi-scale and Nonlinear Problems

*Maureen M. Morton, Stark State College*

**Speaker:****Monday March 25, 2019***
4:00 p.m.
Title: Mathematics of Turbulent Flow and Comparison with Experiments
Speaker: *Bjorn Birnir, University of California, Santa Barbara

**Monday February 18, 2019***
4:00 p.m.
Title: Forecasting U.S. Elections with Compartmental Models of Infection
Speaker: *Alexandria Volkening

**Monday February 18, 2019***
4:00 p.m.
Title: Active Noisy Oscillators – Analytical Approaches, Stochastic Phase Description, and Coupling Effects
Speaker: *Dr. Benjamin Lindner, Department of Physics and Bernstein Center for Computational Neuroscience, Humboldt University (Berlin, Germany)

### Fall 2018

**Monday December 3, 2018**

3:00 p.m.

**Title: ***Mathematical Modeling of Resistance to Anti-Cancer Drugs*

**Speaker: **Nara Yoon, Cleveland Clinic

**Monday November 12, 2018 ***(seminar postponed-new date will follow)*

3:15 p.m.

**Title: ***Shape Versus Timing: Linear Responses of a Limit Cycle with Hard Boundaries Under Perturbation*

**Speaker:** Yanyang Wang, Ohio State University

**Wednesday October 31, 2018**

3:15 p.m.

**Title: ***Chaos and Levy Walks in Swarming Bacteria*

**Speaker:** Gill Ariel, Associate Professor, Bar-llan University

**Monday October, 15 2018**

3:15 p.m.

**Title:** *How Immune Selection can Shape Evolution of Malaria Quasi-Species*

**Speaker:** David Gurarie, Professor, Department of Mathematics, Applied Mathematics, and Statistics; Adjunct, Center for Global Health and Diseases

### Spring 2018

**Monday April 30, 2018**

5:00 p.m., Yost 306

Title: *The Role of Mutual Information in Biology*

Speaker: Andrew Eckford, York University

**Fall 2016**

**Wednesday, September 7, 2016**

3:15 p.m.

Title: Enhancing resolution in inverse problems based on a reduced model (Part 1)

Speaker: Erkki Somersalo (Professor and Interim Chair, Case Western Reserve University)

**Wednesday, September 14, 2016**

3:15 p.m.

Title: Enhancing resolution in inverse problems based on a reduced model (Part 2)

Speaker: Erkki Somersalo (Professor and Interim Chair, Case Western Reserve University)

**Wednesday, September 21, 2016**

3:15 p.m.

Title: Enhancing resolution in inverse problems based on a reduced model (Part 3)

Speaker: Erkki Somersalo (Professor and Interim Chair, Case Western Reserve University)

**Wednesday, September 28, 2016**

3:15 p.m.

Title: Enhancing resolution in inverse problems based on a reduced model (Part 4)

Speaker: Erkki Somersalo (Professor and Interim Chair, Case Western Reserve University)

**Wednesday, October 19, 2016**

3:15 p.m.

Title: Convergent interpolatory quadrature schemes: Part 1

Speaker: Ulises Fidalgo (Lecturer, Case Western Reserve University)

**Wednesday, October 26, 2016**

3:15 p.m.

Title: Convergent interpolatory quadrature schemes: Part 2

Speaker: Ulises Fidalgo (Lecturer, Case Western Reserve University)

### Spring 2020

**January 30, 2020**

Title: *Interleavings and Gromov-Hausdorff Distance***
Speaker: **Jonathan Scott, Cleveland State University

**February 6, 2020**

Title: *The Homotopy Theory and Homotopy Limits of dg-catergories***
Speaker: **Zhaoting Wei, Kent State University

**February 27, 2020**

Title: *Homotopy Limits of dg-catergories 2 ***
Speaker: **Zhaoting Wei, Kent State University

**March 5, 2020**

Title: *Picard Groupoids and Gamma-categories***
Speaker: **Amit Sharma, Kent State University

### Fall 2019

**September 26, 2019 | 2:30 PM | Case Western Reserve University, Yost Hall, 306**

Title:*The Homotopy Theory of Coherently Commutative Monoidal Quasi-Categories***
Speaker:** Amit Sharma (Kent State University)

**October 10, 2019 | 2:30 PM | Kent State University Mathematical Sciences Building, 367**

**Title:** *Simplicial Functor Calculus*

**Speaker:** Rhiannon Griffiths, PhD Candidate (CWRU Department of Mathematics, Applied Mathematics and Statistics)

**October 24, 2019 | 2:30 PM | Case Western Reserve University, Yost Hall, 306**

**Title:** *From the Euler Characteristic of a Category to the Magnitude of Metric Space (and beyond)*

**Speaker:** Mark Meckes, Professor (CWRU Department of Mathematics, Applied Mathematics and Statistics)

**November 7, 2019 | 2:30 PM | Kent State University Mathematical Sciences Building, 367**

**Title:** 2-*Homological Algebra and Picard Cohomology*

**Speaker:** Michael Horst (Ohio State University)

** November 21, 2019 | 2:30 PM | Case Western Reserve University, Yost Hall, 306**Homotopy Theory of Picard Categories

Title:

**Niles Johnson (Ohio State University)**

**Speaker:**

**December 5, 2019 | 2:30 PM | Kent State University Mathematical Sciences Building, 367
**Title:

*Baez-Dolan Stabilization and Bousfield localization without left properness*

**David White (Denison University)**

**Speaker:**

### Spring 2016

**Thursday, April 21, 2016**

10:30 a.m.

Title: Signal Processing and Information Retrieval in Remote Sensing

Speaker: Xiaoxiang Zhu (Professor for Signal Processing in Earth Observation, Technical University of Munich (TUM) & German Aerospace Center (DLR), Germany)

### Spring 2015

**Tuesday, March 24, 2015**

3:00 – 4:00 p.m.

Title: Cellular Telephone Games: How Biological Networks Cope With Noisy Signal Transmission

Speaker: Michael Hinczewski (Case Western Reserve University)

### Spring 2016

**Friday, February 5, 2016**

12:30 p.m.

Title: On the intervention against Schistosomiases: A mathematical modeling work in progress

Speaker: Ramzi Alsallaq (Senior Research Associate, Case Western Reserve University)

**Friday, February 12, 2016**

12:30 p.m.

Title: Modeling Arbovirus Transmission

Speaker: Charles H. King (Professor, Center for Global Health and Disease, Case Western Reserve University)

**Friday, February 26, 2016**

12:30 p.m.

Title: Frontiers in Animal Movement Modeling and Encounter Theory in Ecology

Speaker: Eliezer Gurarie (Quantitative Ecologist, University of Maryland)

**Friday, March 4, 2016**

12:30 p.m.

Title: Quantifying the Interplay Between Structure and Dynamics

Speaker: James Seckler (Postdoctoral Fellow in Pediatrics, Case Western Reserve University School of Medicine)

**Friday, March 18, 2016**

8:15-11:30 a.m. in Yost 306, 12:30-1:45 p.m. in Rockefeller 309

COMSOL Multiphysics, Application Builder and Fluid Flow Workshop

**Wednesday, March 23, 2016**

****4:30 p.m. in Yost 306****

Title: Better Living Through Control: With Applications to Neural and Cardiac Systems

Speaker: Jeff Moehlis (Professor, University of California- Santa Barbara)

**Friday, April 1, 2016**

12:30 p.m.

Title: Multiscale Modeling of Axonal Cytoskeleton Dynamics in Disease

Speaker: Chuan Xue (Assistant Professor, Ohio State University)

**Friday, April 8, 2016**

12:30 p.m.

Title: Structured Recurrent Networks: Two Lessons from Random Matrix Theory

Speaker: Yonatan Aljadeff (Postdoctoral Scholar, University of Chicago)

*Co-sponsored by CWRU’s Institute for the Science of Origins (ISO)*

**Friday, April 22, 2016**

12:30 p.m.

Title: Analysis of Complex Bursting Patterns in Multiple Time Scale Respiratory Neuron Models

Speaker: Yangyang Wang (PhD Candidate, University of Pittsburgh)

**Monday, April 25, 2016**

12:30 p.m.

Title: Psychotroctopus

Speaker: Jonathan Miller (Associate Professor, Physics and Biology Unit, Okinawa Institute for Science and Technology)

### Spring 2024

**4/3/2024**

**Speaker**: Stephen Andryc

**Title**: Geometrically Interpreting Edwards’ Addition Formula

**Abstract**: Elliptic curves are often introduced in the context of real cubic curves, so that the point addition formula can be explained geometrically using intersections with lines. In 2007, Harold Edwards published an incredibly compact and powerful formula for addition on special quartic elliptic curves. In this talk, we will extract a geometric construction underlying Edwards’ formula directly from the familiar process on cubics, in a manner that is made as accessible as possible.

**3/6/2024**

**Speaker**: Dr. David Singer

**Title**: Confocal Families of Conics in the Hyperbolic Plane

**Abstract**: Conics in the hyperbolic plane exhibit much more variety than those in the Euclidean plane. Depending on the author, they have been classified as occurring in nine, eleven, or twelve forms. I will describe a classification of *confocal families *of conics, where a focus can be understood as a source of rays from a point in the plane, an ideal point, or an ultra-ideal point. The presentation will be on an expository level; previous experience with hyperbolic geometry will not be vital for understanding the talk (I hope!)

**3/20/2024**

**Speaker**: Andrew Edwards

**Title**: Weierstrass-Enneper Representations for Minimal Surfaces

**Abstract**: A surface in R^3 is called minimal if its mean curvature is zero at all points. The classical examples of minimal surfaces are the catenoid and the helicoid. Constructing more complicated minimal surfaces can be difficult, but a useful tool for doing so is the Weierstrass-Enneper representation, which uses principles of complex analysis to generate minimal surfaces.

**3/27/2024**

**Speaker**: Reeve Johnson

**Title**: The Problem(s) with Malfatti’s Marble Problem (but also, the Solution(s))

**Abstract**: In 1803 the Italian mathematician Gian Francesco Malfatti posed a problem: maximize the volume of three circular columns cut out of a triangular slab of marble with fixed height. He also proposed a solution: three circles within the triangle, each tangent to one another, should do the trick. His solution remained unquestioned for many years, simply because it *looked* correct. But, in 1967, somebody clocked his tea- Malfatti’s solution was not only incorrect in some cases, it was incorrect in EVERY case! In 1994, the correct solutions were found and, in 2022, those solutions were fully proved. Ok great! But there’s more… Why do we call his (incorrect) solution the “Malfatti circles” when, 30 years earlier in Japan, Naonobu Ajima examined the geometry of this exact same arrangement of three circles within a triangle? What exactly did Ajima determine about these circles? Did Malfatti know about Ajima? This talk will address these questions along with questions about proofs, sacred Japanese temple geometry, and so much more.

### Fall 2015

**Monday, September 21, 2015**

3:30 p.m.

Title: Elastic Curves in Euclidean space

Speaker: David Singer (Professor and Interim Chair, Mathematics, Applied Mathematics, & Statistics, Case Western Reserve University)

**Monday, September 28, 2015**

3:30 p.m.

Title: Elastic Curves in Manifolds

Speaker: David Singer (Professor and Interim Chair, Mathematics, Applied Mathematics, & Statistics, Case Western Reserve University)

**Monday, October 12, 2015**

3:30 p.m.

Title: Elastic Rods

Speaker: David Singer (Professor and Interim Chair, Mathematics, Applied Mathematics, & Statistics, Case Western Reserve University)

### Fall 2015

**Monday, August 24, 2015**

3:15 p.m.

Title: Disease Invasion on Community Networks

Speaker: Joe Tien (Assistant Professor, Ohio State University)

**Friday, September 4, 2015**

3:15 p.m.

Title: Interval Timing and Decision Making with an Opponent Poisson Diffusion Model

Speaker: Patrick Simen (Assistant Professor, Oberlin College)

**Monday, September 21, 2015**

3:15 p.m.

Title: Immune Selection of Malaria Quasi-Species: A Modeling Perspective

Speaker: David Gurarie (Professor, Case Western Reserve University)

**Monday, September 28, 2015**

3:15 p.m.

Title: Collective Dynamics in Ant Raids

Speaker: Shawn Ryan (Postdoctoral Research Associate, Kent State University)

**Monday, October 26, 2015**

3:15 p.m.

Title: Assessing Darwinian Selection in Tumors From Molecular “Big Data”

Speaker: Thomas LaFramboise (Associate Professor, Case Western Reserve University)

**Monday, November 2, 2015- ***Postponed*****

3:15 p.m.

Title: TBA

Speaker: Harihara Baskaran (Professor, Case Western Reserve University)

**Joint Colloquium/MLSS**

**Joint Colloquium/MLSS**

**Monday, November 9, 2015**

3:15 p.m.

Title: Stochastic and deterministic models of biochemical reaction networks

Speaker: David Anderson (Associate Professor, University of Wisconsin)

**Monday, November 16, 2015**

3:15 p.m.

Title: Do marine organisms hedge their bets? or A tragic tale of a diffusion approximation gone astray, with hope for redemption

Speaker: Robin Snyder (Associate Professor, Case Western Reserve University)

**Joint Colloquium/MLSS**

**Monday, November 23, 2015**

3:00 p.m.

Title: Collective Dynamics: Modeling, Analysis and Simulations

Speaker: Marie-Therese Wolfram (Radon Institute for Computational and Applied Mathematics)

**Wednesday, December 2, 2015**

3:15 – 4:15 p.m.

Title: Time-Series from Ventilated Patients and Dynamics of the Pulmonary Infection/Immunity Process

Speaker: Todd Young (Professor of Mathematics, Ohio University)

### Spring 2015

**Wednesday, March 18, 2015**

3:15 – 4:15 p.m.

Title: Mathematical Model of Volume Phase Transition in Polyelectrolyte Gels

Speaker: Lingxing Yao (Case Western Reserve University)

**Monday, March 23, 2015**

3:15 – 4:15 p.m.

Title: Amoeboid Cell Migration: Recent Experiments and Proposed Modeling

Speaker: Wanda Strychalski (Case Western Reserve University)

**Monday, March 30, 2015**

3:15 – 4:15 p.m.

Title: Efficient Control of Schistosomiasis in Endemic Communities: Modeling In-Host Biology, Demographics, Diagnostics and Interventions

Speaker: Nara Yoon (Case Western Reserve University)

**Monday, April 6, 2015**

3:15 – 4:15 p.m.

Title: **Mathematical modeling of sexually transmitted diseases**

Speaker: Ramzi Alsallaq (New York University

**Monday, April 13, 2015**

3:15 – 4:15 p.m.

Title: Data-Driven Modeling of Living Fluids

Speaker: Greg Forest (The University of North Carolina at Chapel Hill)

**Monday, April 20, 2015**

3:15 – 4:15 p.m.

Title: The Role of Long Range Coupling in the Crayfish Swimmeret System

Speaker: Lucy Spardy (The Ohio State University, Mathematical Biosciences Institute)

**Monday, April 27, 2015**

3:15 – 4:15 p.m.

Title: Dynamics of Neurons and Field Potentials in the Auditory Brainstem

Speaker: Joshua Goldwyn (The Ohio State University)