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)
Title: Limit theorems for mixed-norm sequence spaces with applications to volume distribution II

October 31, 2023
Speaker: Michael Juhos (University of Passau, Germany)
Title: Limit theorems for mixed-norm sequence spaces with applications to volume distribution

October 17, 2023
Speaker: Michael Roysdon
Title: Framework for the Theory of Higher Order Convex Bodies III

October 3, 2023
Speaker: Michael Roysdon
Title: Framework for the Theory of Higher Order Convex Bodies II

September 26, 2023
Speaker: Ulises Fidalgo
Title: A Riemann-Hilbert problem to study the strong asymptotic behavior of multi-orthogonal polynomials.

September 12, 2023
Speaker: Michael Roysdon
Title: Framework for the Theory of Higher Order Convex Bodies

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

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
Title: Numerical Methods for Simulating Fluid-Structure Interaction Problems in Biology
Abstract: 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.

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.

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.

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

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

Spring 2019

Monday April 29, 2019
4:00 p.m.
Title: Shape Versus Timing: Linear Responses of a Limit Cycle with Hard Boundaries Under Perturbation
Speaker: Yangyang Wang, Mathematical Biosciences Institute

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
Speaker: Maureen M. Morton, Stark State College

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
Title: Homotopy Theory of Picard Categories
Speaker: Niles Johnson (Ohio State University)

December 5, 2019 | 2:30 PM | Kent State University Mathematical Sciences Building, 367
Title: Baez-Dolan Stabilization and Bousfield localization without left properness
Speaker: David White (Denison University)

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

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)