UB Applied Mathematics Seminar
Tuesdays in Math 250 from 4:00-4:50pm (tea upstairs at 3:30).
Year -
2019-2020,
2018-2019,
2017-2018,
2016-2017,
2015-2016,
2014-2015,
2013-2014,
2012-2013,
2011-2012,
2010-2011
Fall 2019
September 10
Title: A Gillespie algorithm for non-Markovian renewal processes
Abstract: The Gillespie algorithm is a tool for exactly simulating event-driven stochastic dynamics (interacting point processes). As recent research on temporal networks has demonstrated, inter-event times of various human activities, among others, obey long-tailed distributions, violating the Poissonian assumption underlying the basic Gillespie algorithm. Starting from some introduction to temporal networks, I will present a new Gillespie algorithm for renewal processes which are not necessarily Poisson processes. The algorithm crucially exploits properties of the Laplace transform. It is applicable to renewal processes whose survival function of inter-event times is a completely monotone function. It works faster than a previously proposed algorithm and is exact for an arbitrary number of processes running in parallel.
October 1
Title: Complex Decision Making for Autonomous Materials Development
Abstract: Decision-making is an important part of autonomous materials development because a robot scientist must decide which experiments to perform to achieve an overall experimental objective, subject to physical and process constraints, based on a limited set of noisy data. In this talk, I review a broad set of decision-making techniques and models used throughout autonomous and semi-autonomous materials research systems. I will start with an introduction to the exploration-exploitation problem, and then discuss heuristic approaches to decision-making before introducing more formal techniques such as Bayesian optimization and reinforcement learning. Throughout, I will highlight how experimental constraints necessitate considerations other than information theoretic ones, and show how such constraints are modeled. Examples of our work on specific autonomous materials systems will also be provided.
October 8
Title: Hierarchical Dense Subgraph Discovery: Models, Algorithms, Applications
Abstract: Abstract: Finding dense substructures in a network is a fundamental graph mining operation, with applications in bioinformatics, social networks, and visualization to name a few. Yet most standard formulations of this problem (like clique, quasi-clique, densest at-least-k subgraph) are NP-hard. Furthermore, the goal is rarely to find the “true optimum” but to identify many (if not all) dense substructures, understand their distribution in the graph, and ideally determine relationships among them. In this talk, I will present a framework that is designed to find dense regions of the graph with hierarchical relations. Our model can summarize the graph as a tree of subgraphs and generalizes two widely accepted dense subgraph models; k-core and k-truss decompositions. We present practical sequential and parallel local algorithms for our framework and empirically evaluate their behavior in a variety of real graphs. Furthermore, we adapt our framework for bipartite graphs, which are used to model group relationships such as author-paper and user-product relations, and heterogeneous networks with node/edge attributes. We demonstrate how proposed algorithms can be utilized for the analysis of a citation network and a user-product network of the Amazon Kindle books.
Bio: A. Erdem Sariyuce is an Assistant Professor in Computer Science and Engineering at the University at Buffalo. Prior to that, he was the John von Neumann postdoctoral fellow at Sandia National Laboratories. Erdem received his Ph.D. in Computer Science from the Ohio State University. He conducts research on large-scale graph mining with a particular focus on practical algorithms to explore and process real-world networks. In the past, Erdem received the Best Paper Runner-up Award at the International World Wide Web Conference (WWW) in 2015.
October 22
Title: Five Conservative Regularizations of the Hopf Equation
Abstract: The Hopf equation, also known as the inviscid Burgers equation, is the
simplest nonlinear wave equation and an introductory example for
students studying hyperbolic, quasi-linear partial differential
equations. The initial value problem exhibits finite time singularity
formation (gradient catastrophe), which can be regularized in many
ways. One common approach that is inspired by physical problems,
e.g., gas dynamics, is to add higher order, dissipative smoothing
terms and study the zero dissipation limit. Under quite general
conditions, this vanishing-viscosity technique offers both
mathematical and physical justifications for weak (entropy) solutions
and the Rankine-Hugoniot conditions for compressive shock waves. A
completely different approach is to add higher order, conservative
(dispersive) terms and study the small dispersion limit. This talk
will present five distinct, physical, conservative regularizations
that yield different small dispersion behavior for initial value
problems. A rich variety of dispersive shock wave solutions for these
models will be analyzed using nonlinear wave (Whitham) modulation
theory, numerical simulation, and experiment. All conservative
regularizations considered result in solutions that significantly
deviate from the vanishing-viscosity approach.
Spring 2020
February 4
Title: Bio Mathematics: modeling of tissue growth and vascular networks
Abstract: In this talk I will describe two problems of interest in the area of bio-mathematics: tissue growth of tissue engineered articular cartilage and the modeling of the retinal vasculature.
In the articular cartilage problem, an hybrid model is developed to account for the effect of porosity in a cartilage tissue-engineered construct. The model couples a discrete description of the chondrocytes (cells) to a continuum phenomenological approach for the components of the extracellular matrix, nutrients, and scaffold. The model investigates the effect of porosity and the potential application of growth factors, and provides a new framework to couple porosity with individual cellular dynamics for the growth of tissue in cell-seeded scaffolds.
In the retinal vasculature problem, a reduced order model, leveraging the analogy between current in an electric circuit and blood in the vasculature, is developed to study the effect of several biological factor on the retinal circulation.. The relevance of the factors related to ocular pathologies, with a particular focus on glaucoma, is investigated.
February 25
Title: Network Analysis of Maximum a Posteriori (MAP) Detectors for Sensor Design
Abstract: Malicious attack detection, assessment, mitigation challenges are increasingly arising in networks that are tightly coupled with cyber (computation and communication) and physical components. In the recent past, researchers have proposed several model- and heuristic-based models for detecting and mitigating attacks against the actuators/sensors in the network. Despite the success of these studies in revealing the performance and limitations of attack detectors, several challenges remain, particularly in distinguishing malicious signals from ambient data, selecting sensor locations to maximize the detection performance and deriving graphical rubrics to evaluate and optimize network security.
In this talk, I will present our recent work on the performance characterization of a class maximum-a-posteriori (MAP) detectors for network systems driven by unknown stochastic inputs, as a function sensor locations and the topology of the network. First, starting from some introduction to statistical hypothesis testing in state-space systems, I will discuss key ideas that we leveraged from the theory of Toeplitz operators to obtain the closed form expressions for the performance of MAP detectors. Next, I will highlight how these expressions may be used to derive conditions under which the detection performance may improve or deteriorate as the graphical distance between the input nodes and the sensors location increases. Our results provide structural insights into the sensor placement from a detection-theoretic viewpoint.
TBD
March 3 (Tuesday)
Title: The Structure and Interpretation of Graph Spectral Densities
Abstract: In this talk, we describe the analysis of graphs via
global summaries of the eigenvalue distributions and eigenvector
behavior. Our approach is drawn from the condensed matter physics
literature, where the idea of local and global densities of states is
often used to understand the electronic structure of systems, and we
describe how these densities play a common role in such seemingly
disparate topics as spectral geometry, condensed matter physics, and
the study of centrality measures in graphs. We then discuss how
structural motifs manifest in the spectrum, give fast algorithms to
estimate spectral densities, and conclude with a discussion of some of
our current research directions in applying these tools to the
analysis of large-scale graphs.
March 24 (Tuesday)
Title: Exact topological inference on resting-state functional brain networks
Abstract: Advances in functional magnetic resonance imaging (fMRI) enable us to measure spontaneous fluctuations of neural signals in the human brain in higher spatial and temporal resolutions than before. Many previous studies on resting-state fMRI have mainly focused on the topological characterization of graph theory features that depends on the network scale and edge weight thresholding. Persistent homology provides a more coherent mathematical framework that is invariant to the parameter changes. Instead of looking at networks at a fixed scale, persistent homology charts the network changes in topological features such as Betti numbers over every possible scale. In doing so, it reveals the most persistent topological features that are robust to parameter and noise. In this talk, the exact probability distribution on the Betti numbers that are used in determining the statistical significance will be discussed Two open problems related to Betti numbers over graph filtration will be presented as well. This talk is based on Network Neuroscience 3:674-694.
Shortbio: Moo K. Chung, Ph.D. is an Associate Professor in the Department of Biostatistics and Medical Informatics at the University of Wisconsin-Madison (http://www.stat.wisc.edu/~mchung). He is also affiliated with the Waisman Laboratory for Brain Imaging and Behavior. Dr. Chung’s research focuses on persistent homology, computational neuroimaging and brain network analysis, His research concentrates on the methodological development required for quantifying and contrasting functional, anatomical shape and network variations in both normal and clinical populations using various mathematical, statistical and computational techniques. He has published three books on neuroimage computation including Brain Network Analysis that was published through Cambridge University Press in 2019.
April 14
Title: Mathematics of an epidemiology-genetics model for assessing the role of insecticides resistance on malaria transmission dynamics
Abstract: The widespread use of indoors residual spraying (IRS) and insecticides-treated bednets (ITNs) has led to a dramatic reduction of malaria burden in endemic areas. Unfortunately, such usage has also resulted in the challenging problem associated with the evolution of insecticide resistance in the mosquito population in those areas. Thus, it is imperative to design malaria control strategies, based on using these (IRS- and ITNs-based) interventions, that reduce malaria burden while effectively managing insecticide resistance in the mosquito population. This talk describes the use of a model that couples malaria epidemiology with mosquito population genetics to explore control scenarios.
April 21
April 28
Title: Anisotropic collapse in three-dimensional dipolar Bose-Einstein condensates
Abstract: We study the (3+1)-dimensional Gross-Pitaevskii / Nonlinear Schrödinger equation describing a Bose-Einstein condensate with negative dipolar strength. Bound states are computed using accurate numerical techniques for a wide range of nonlinear frequencies. We find that the mapping between the total number of atoms (mass) and nonlinear frequency is multi-valued and possesses a cusp point, which corresponds to a ``candlestick" ground state. Direct simulations of this ground state exhibit strongly-anisotropic collapse. A self-similar theory is proposed to describe this dynamics. This is joint work with Jessica Taylor.
Fall 2018
September 18
Title: Bayesian models of stereotyping and social categorization
Abstract: Identities are the labels we use to categorize ourselves and others. Examples of identities include social roles, like ``doctor’’ and ``mother,’’ and group memberships, like ``Democrat’’ or ``Yankees fan’’. It is generally accepted that the ways we label (or categorize) ourselves and others with identities, and the ways others label us both impact our behavior. However, our ability to predict these labeling decisions, and the ensuing social behaviors that depend on them, is still largely limited to qualitative models of social cognition. I will present a string of recent efforts on formalizing the ways in which we stereotype and then categorize others, and how those categorizations then lead to social behaviors. I will also detail how I have leveraged these formalizations in empirical work on both social media and survey data.
October 2
Title: The Foundations and Frontiers of Cognitive Neuroengineering
Abstract: Cognitive neuroengineering is the intersection of cognitive neuroscience and neuroengineering. In cognitive neuroscience, we use many methods to measure real-time cognitive and neural activity. In neural engineering, we can stimulate and monitor changes in neurophysiological and cognitive activity in real-time contexts. In tandem, time-efficient algorithms are available to rapidly model input-output associations between brain stimulation, neural activity and measured behavior. Given these technologies, we can use conventional and emerging approaches from control engineering – a branch of systems engineering – to address pervasive problems in neuromodulation in experimental and clinical contexts. We can draw from cognitive neuroscience, engineering, and network science to confront these challenges.
October 9
October 16
Title: A Kinetic Description for Morphing Continuum
Abstract: The coupling between the intrinsic angular momentum and the hydrodynamic linear momentum has been known to be prominent in fluid flows involving physics across multiple length and time scales, e.g. turbulence, nonequilibrium flows and flows at micro-/nano-scale. Since the classical Navier-Stokes equations and Boltzmann’s kinetic theory are derived on the basis of monatomic gases or volumeless points, efforts to derive constitutive equations involving intrinsic rotation for fluids of polyatomic molecules have been found since the 1960s. One of the proposed continuum theories for polyatomic molecules was Morphing Continuum Theory (MCT). The theory was originally formulated under the framework of rational continuum mechanics and thermodynamic irreversible processes. The mathematically rigorous continuum mechanics presents a complete and closed set of governing equations, but leaves the physical meanings unexplained. Similar to the correlation between Boltzmann's kinetic theory and the classical continuum mechanics, an advanced kinetic theory involving the Boltzmann-Curtiss (B-C) distribution function and the B-C equation will be introduced for a morphing continuum. The method of the most probable distribution method is used to derive the Boltzmann-Curtiss distribution. The corresponding Boltzmann-Curtiss equations will be demonstrated to be the MCT governing equations without any dissipation terms, i.e. the system (flows with inner structures) is in equilibrium and at the Boltzmann-Curtiss distribution. A first-order approximation to the B-C distribution will be used to further derive the B-C transport equations. The corresponding governing equations will then be compared with the MCT equations. Furthermore, a path to reduce the presented MCT equations down to the classical N-S equations will be demonstrated and discussed.
October 23
October 30
Title: Simplicial closure and simplicial diffusions
Abstract: Networks are a fundamental abstraction of complex systems throughout the sciences and are typically represented by a graph consisting of nodes and edges. However, many systems have important higher-order interactions, where groups of nodes interact simultaneously, and such higher-order relations are not captured by a graph containing only pairwise connections. In the first part of the talk, we will explore the rich variety of higher-order interaction structure in empirical datasets and evaluate how well we can predict the appearance of new higher-order interactions, or what we call simplicial closure events. In the second part of the talk, we develop a model of diffusion for these higher-order interaction datasets. The key idea is to generalize the well-known relationship between the normalized graph Laplacian and random walks on graphs by devising an appropriate normalization for the Hodge Laplacian, the analog of the graph Laplacian for simplicial complexes. We can then use combinatorial Hodge theory to decompose the diffusions into components that reveal different types of structure. Throughout the talk, we will examine several real-world datasets, which come from social, biomedical, communication, human mobility, and commerce systems.
November 6
Title: Tracking the Evolution of Dynamic Networks
Abstract: To quantify the evolution of dynamic networks, one needs a notion of temporal
difference that captures significant structural changes between two successive instants. We describe existing distances between graphs, and study their ability to reveal organizational changes. We propose a novel distance that can detect changes occurring on a graph at multiple scales. We develop a fast randomized algorithm to compute an approximation to this novel graph distance. We apply this novel distance to the analysis of a dynamic community graph. We detect the time at which the graph dynamics switches from a normal evolution -- where balanced communities grow at the same rate -- to an abnormal behavior -- where communities start merging. This is work in collaboration with Dr. Nathan Monnig, and Dr. Peter Wills.
November 13
Title: Graph product multilayer networks: spectral properties and applications
Abstract: This talk will introduce theoretical foundations of graph product multilayer networks (GPMNs), a family of multilayer networks that can be obtained as a graph product of two or more factor networks. Cartesian, direct (tensor), and strong product operators are considered, and then generalized. We first describe mathematical relationships between GPMNs and their factor networks regarding their degree/strength, adjacency, and Laplacian spectra, and then show that those relationships can still hold for non-simple and generalized GPMNs. We will also discuss applications of GPMNs in four areas: predicting epidemic thresholds, modelling propagation in non-trivial space and time, analysing higher-order properties of self-similar networks, and formulating evolutionary dynamics of organism-environment couplings.
Spring 2019
March 28, 2019 (Rm 250, 4:00PM)
Title: Solitary waves and collisions in the strongly nonlinear β-Fermi-Pasta-Ulam-Tsingou chain
Abstract: I will discuss recent theoretical and numerical work in the β-FPUT system. This system, the study of which jump-started the modern field of numerical experimentation in physics, consists of a mass-spring chain which has both a quadratic and a nonlinear (here, quartic) term in its potential. Its equation of motion admits no general solution though approximate solutions can be made in the weakly nonlinear limit.
I will present methods to obtain an approximate analytic solution in the strongly nonlinear limit . In this limit, energy transport takes the form of a wave pulse which is nearly a solitary wave, followed by a small oscillatory tail. Finally, I will compare numerical simulations of collisions between wave pulses using both the exact solution and an analytic solution.
This work has benefited from partial support from the Fulbright-Nehru Fellowship to Surajit Sen. Alexandra Westley has been a Presidential Fellow during her PhD work at SUNY Buffalo.
April 2, 2019
Title: Anti-regular graphs as seen from within threshold graphs
Abstract: A graph is called anti-regular if only two vertices in the graph have equal degree. An anti-regular graph is an example of a threshold graph; the latter were introduced by Chvatal and Hammer in 1977 and since then have found numerous applications in computer science and psychology. Threshold graphs can be recognized in linear time and it has been recently proved that the spectrum of a threshold graph is a complete invariant within the family of threshold graphs. In this talk, we will present the state of the art on the spectral properties of threshold graphs and present recent results on the role of the eigenvalues of anti-regular graphs as seen from within the family of threshold graphs.
April 11, 2019 (Rm 250, 3:50PM)
Title: Focusing nonlinear Schroedinger equations with nonvanishing boundary conditions
Abstract: In this talk we review the scattering theory of the focusing 1+1 AKNS system with symmetric nonvanishing boundary conditions. We focus on triangular representations of fundamental eigensolutions and Jost solutions, two types of Marchenko integral equations, reflectionless solutions, and connections to the matrix Schroedinger equation.
April 16, 2019
Title: Triad Closure in Coevolving Network Systems
Abstract: Coevolving network systems are a framework for modeling the interplay between network evolution and nodal dynamics. In these systems, nodal states coevolve with the network topology, and they have found extensive applications in modeling contagion diffusion on networks. A feature that has not been extensively studied in coevolving networks setting is the influence of triad closure on contagion dynamics. I will present novel coevolving networks models of SIS epidemics and opinion formation which incorporate triad closure and provides a unique opportunity to explore the role of triad closure in the epidemic spread and opinion formation. Furthermore, I will discuss the state-of-the-art analytical methods for studying coevolving networks and present derivation of approximate master equations for the analysis of coevolving networks with triad closure.
April 30, 2019
Title: Musical understanding with sets, groups, and distributionsBA
Abstract: Set theory and group theory play key roles in our current speculative understanding of music. This talk will give an overview on a few contemporary topics in mathematical music theory — maximally even sets, voice-leading spaces, and neo-Riemannian transformational theory — and then dive deeply into the dynamic system called FiPS that models musical spaces using maximally even sets that change over time.
May 7, 2019
Title: Sparse spectral element methods for the helically reduced Einstein equations
Abstract: We describe efforts, based on spectral element methods, towards the numerical
construction of 2-body solutions to the Einstein equations reduced by helical
symmetry. Heuristically, the helical reduction is an initial data+evolution
synthesis. This nonstandard formulation involves a mixed-typed operator L, and
our solution process relies on relaxation through a Broyden-Krylov approach.
The computational domain which surrounds the compact objects is split into 15+
subdomains (blocks, spherical shells, and cylindrical shells on which we use
classical spectral expansions). Half of talk will focus on numerical linear
algebra, and in particular fast inversion of our subdomain approximations of L,
either through modal-based preconditioning or direct solves.
Fall 2017
September 5 Jose Carrillo (Imperial College - London) - Talk starts at 3:30 pm
Title: Swarming, Interaction Energies and PDEs
Abstract: I will present a survey of the main results about first and second order models of swarming where repulsion and attraction are modeled through pairwise potentials. We will mainly focus on the stability of the fascinating patterns that you get by random particle simulations, flocks and mills, and their qualitative behavior. Qualitative properties of local minimizers of the interaction energies are crucial in order to understand these complex behaviors. Compactly supported global minimizers determine the flock patterns whose existence is related to the classical H-stability in statistical mechanics and the classical obstacle problem for differential operators.
September 12 Vitali Vougalter (University of Toronto)
Title: On the solvability of some systems
of integro-differential equations with anomalous diffusion
Abstract: The work deals with the existence of solutions
of a system of integro-differential equations in the case of anomalous
diffusion with the Laplacian in a fractional power. The proof of
existence of solutions is based on a fixed point technique.
Solvability conditions for non Fredholm elliptic operators in unbounded
domains are used.
September 18, 19 and 20. Myhill Lecture Series by Guoliang Yu (Texax A & M)
September 26 Gourab Ghoshal (University of Rochester)
- Cancelled
October 3 Jie Sun (Clarkson University)
Title: Computational Network Inference from Data
Abstract: Understanding the dynamics and functioning of complex systems is one of the most challenging tasks faced in modern science. A central problem to tackle is to accurately and reliable infer the underlying cause-and-effect (i.e., causal) network from observational data, especially when the system consists of a large number of interacting components and the dynamics can be intrinsicaly nonlinear.
In this talk I will review my recent collaborative projects on optimal causation entropy (oCSE) as a general framework to reconstruct networks (whose edges are hidden) from data measured on the nodes. Depending on the context, the framework can be adapted to incorporate prior information of noise distributions, and also to accommodate both longitudinal and non-longitudinal data.
I will show results of applying oCSE to synthetic datasets (as benchmark) as well as real-world datasets in several different disciplines. Examples of application include discovering ``social” interaction in swarming insects, detecting structural patterns and damages in bridges, as well as fitting Boolean functions to genotype-phenotype data. Time permits I will also discuss a few other related problems, including data fusion network reconstruction, uncertainty quantification, and visualization of bipartite network data.
October 10 Dane Taylor (UB)
Title: Centrality analysis and community detection for temporal and multilayer networks
Abstract: The social and biological sciences often give rise to datasets represented by multilayer networks in which different layers encode different types of interactions. In particular, many networks are time-varying and can be modeled as a temporal sequence of layers. Despite their commonality, the mathematical foundations for such data structures are not well established. I will present my recent work in this area for two network-analysis methodology classes. First, I will present a temporal generalization of eigenvector-based centrality measures (e.g., PageRank), giving a tunable framework to analyze the importances of network nodes over time. As case studies, we examine the fame of actors during the Golden Age of Hollywood and department prestige for academic institutions. We also conduct a singular perturbation analysis to provide insight toward 'time averaging' for this framework. Next, I will describe the detection of small-scale communities in temporal networks, which is a paradigmatic problem in cybersecurity for detecting anomalies such as fraud and intrusions. To provide theoretical guidance, we develop random-matrix theory to analyze phase transitions in which the dominant eigenvectors of modularity matrices localize onto the communities, thereby allowing their detection. We propose and address a foundational question by asking when is it beneficial to preprocess a temporal network by first aggregating the layers into time windows. We find that layer aggregation via summation and thresholding can be effectively used as a preprocessing filter to allow super-resolution detection of communities that are otherwise too small to detect. This work paves the way for further 'holistic' research that simultaneously considers the network-preprocessing and network-analysis steps.
October 17 Xudan Luo (UB)
Title: Soliton dynamics in the Korteweg-de Vries (KdV) equation with step boundary conditions
Abstract: The long time evolution of initial data consisting of solitons and a positive or negative step are considered for the Korteweg-de Vries (KdV) equation. The positive/negative step evolves into a rarefaction wave/dispersive shock wave that either transmits or traps the solitons within its interior. For the case of solitons passing through a step, the phase shift is calculated. Solitons can also become trapped, in this case the corresponding eigenvalues of the Schr\"odinger equation are embedded in the continuous spectrum.
October 24 Matthew J. Hoffman (RIT)
Title: Estimating Hydrodynamic Flows through Data Assimilation and Tracking Plastic Pollution in the Great Lakes
Abstract: Numerical hydrodynamic forecasts similar to weather forecasts are used operationally in bodies of water such as the Chesapeake Bay and the Great Lakes to predict biogeochemical variables as well as transport. Achieving the best forecasts requires not just improving the numerical model, but combining the modeled output with observational data through data assimilation. I will talk about data assimilation and the application to operational forecasts in Chesapeake Bay and Lake Erie. Data assimilated products could also improve results of transport studies, such as a project of mine estimating the fate of plastic pollution in the Great Lakes. I will discuss our modeling of plastic input and transport through out the entire Great Lakes system.
October 31 Gino Biondini (UB)
Title: A unified approach to boundary value problems
Abstract: Over the last twenty years, a unified approach has been developed by
A.S. Fokas and collaborators to solve boundary value problems (BVPs) for
integrable nonlinear partial differential equations (PDEs). The
approach is a generalization of the inverse scattering transform (IST),
which was originally developed in the 1970's to solve initial value
problems for such PDEs.
Interestingly, however, the approach also provides a novel and powerful
way to solve BVPs for linear PDEs. This talk aims to provide an
introduction to this method for BVPs for linear PDEs. Specifically, I
will describe in detail the solution of BVPs for linear evolution PDEs
in one spatial and one temporal dimension. After presenting the method
in general, a few concrete examples will be considered. Time
permitting, two-point IBVPs, multi-dimensional PDEs and BVPs for linear
elliptic PDEs will also be discussed.
This talk is intended for a broad audience, and will contain no original
results.
November 7 Sonjoy Das (UB MAE)
- Cancelled
November 14 Gino Biondini (UB)
- Cancelled
November 22 - November 25 - UB Fall Recess
November 28 Katharine (Kate) Anderson (Carnegie Mellon University)
- Cancelled
Title: Skill networks and measures of complex human capital
Abstract: We propose a novel, network-based method for measuring worker skills. We demonstrate the method using data from an online free- lance website. Using the tools of network analysis, we divide skills into endogenous categories based on their relationship with other skills in the market. Workers who specialize in these different areas earn dramatically different wages. We then show that in this mar- ket, network-based measures of human capital provide more insight into wages than traditional human capital measures. In particular, we show that workers with diverse skills earn higher wages than those with more specialized skills. Moreover, we can distinguish between two different types of workers benefiting from skill diversity: jacks- of-all-trades, whose skills can be applied independently on a wide range of jobs, and synergistic workers, whose skills are useful in combination and fill a hole in the labor market. On average, workers whose skills are synergistic earn more than jacks-of-all-trades. This framework has the potential to reduce friction in online job markets, improve employer-employee matches, and guide worker training and marketing decisions.
Spring 2018
February 6 Jiwei Zhao (UB Biostatistics)
February 14 (Wed) 4pm - Weiran Sun (Simon Fraser University)
Title: Global Well-Posedness of the Non-Cutoff Boltzmann Equation
with Polynomial Decay Perturbations
Abstract: In this talk we will present our recent work on the global well-posedness of the non-cutoBoltzmann equation with hard potentials. The solution considered is near equilibrium where
the deviation has a polynomial decay. The main step is to show a closed energy estimate for
small data. This is achieved by combining methods of moment propagation, spectral analysis
of the linearized operator, and smoothness ect starting from data with weak regularity. This
is a joint work with Alonso, Morimoto, and Yang.
March 13 Guo Deng (UB)
UB Spring break, March 19 - March 24
April 3 Barbara Prinari (Univeristy of Colorado, Colorado Springs)
Title: Integrable systems, solitons and the inverse scattering transform
Abstract: The study of physical phenomena by means of mathematical
models often leads to a certain class of nonlinear differential
equations referred to as integrable systems. Over the last fifty
years, the study of these equations has attracted considerable
interest because it offers a unique blend of interesting mathematics
and concrete physical applications. Understanding the properties of
these equations, their solutions and their surprisingly rich
mathematical structure often requires a combination of techniques from
different branches of mathematics. After a brief introduction to the
subject, I will review some of my main results in this field.
Specifically, I will discuss the following kinds of problems: (i)
development of the inverse scattering transform (IST) for scalar,
vector and matrix nonlinear Schrodinger (NLS) systems with non-zero
boundary conditions; (ii) soliton interactions in coupled NLS systems;
(iii) development of the IST for integrable systems in two spatial and
one temporal dimension.
April 12/19 Shi Jin (University of Wisconsin Madison)
Fall, 2016
Oct 4: Alethea Barbaro (Case Western Reserve University)
Title: A Phase Transition in a Model for Gang Territorial Development
Abstract: Spray-painting a gang's graffiti around the neighborhood is a job which is often relegated to the youngest members of the gang. However, this is one of the main ways for a gang to lay claim to an area. In this talk, we examine a model for territorial development based on this mechanism. We employ an agent-based model for two gangs, where each agent puts down graffiti markings and moves to a neighboring site, preferentially avoiding areas marked by the other gang. We observe numerically that the systems undergoes a phase transition from well-mixed to segregated territories as the intensity of the avoidance of the other gang's graffiti is varied. We then derive a system of macroscopic PDEs from the model and examine the phase transition in the context of the continuum system.
Oct 25: He Yang (Ohio State University)
Title: Inverse Problem and Optimization in Medical Imaging
Abstract: In the first part of the presentation, I will discuss an inverse problem of x-ray computed tomography (CT) with applications in radiation therapy. The inverse problem is about image reconstruction to compute the attenuation coefficients inside the human body. We investigated several three-dimensional image reconstructions under different system designs. By evaluating the quality of image reconstruction results based on image registrations, we picked the best design for an extremely rapid radiation therapy system.
In the second part of the presentation, I will discuss deep learning technique which is an optimization procedure to study the representations of medical images. In particular, we developed a deep convolutional neural network (CNN) and applied such CNN to thoracic CT images for the classification of lung nodules. I will present the architecture of our deep CNN as well as some results about comparative studies on different CT scan datasets.
Nov 3: Katharine (Kate) Anderson (Carnegie Mellon University)
- Cancelled
Nov 10: Pavel Lushnikov (University of New Mexico)
- Note that the seminar is on Thursday.
Title: Formation of limiting Stokes wave from non-limiting wave
Abstract: Stokes wave is the fully nonlinear periodic gravity wave parameterized by its height. Wave of greatest height has the limiting
form with 120 degrees angle on the crest as found by Stokes in 1880. We consider a conformal map of a free fluid surface of
Stokes wave into the real line with fluid domain mapped into the lower complex half-plane. Stokes wave is fully characterized by
the complex singularities in the upper complex half-plane. The only singularity in the physical sheet of Riemann surface of
non-limiting wave is the square-root branch point located on the imaginary axis. Crossing corresponding branch cut defines the
second sheet of the Riemann surface, which has a singularity in lower complex half-plane. We found the infinite number of square
root singularities in infinite number of non-physical sheets of Riemann surface. Increase of the height of the Stokes wave means
that all these singularities simultaneously approach the real line from different sheets of Riemann surface and merge together
forming 2/3 power law singularity of the limiting wave. It was conjectured (Journal of Fluid Mechanics, v. 800, pp. 557-594 (2016)) that non-limiting
Stokes wave at the leading order consists of the infinite product of nested square root which form the infinite number of sheets
of Riemann surface.
Nov 15: Misun Min (Argonne National Lab)
Title: Scalable High-Order Simulations for PDEs and Applications
Abstract: I will present recent development and analysis on performance characteristics
that impact the scalability of electromagnetic and fluid simulations on large-scale parallel
computers including multi-GPU and many-core architectures.
Discussions include highly-tuned implementation and fast, efficient algorithms based on
high-order spectral element discretizations for solving convection-diffusion type equations
arising in semiconductor and ionic channel applications, as well as classical and quantum
mechanical modelling approaches for simulating electromagnetic systems such as quantum
dots for nanoscale devices and particle accelerators.
Spring 2017
Feb 7 Greg Forest (University of North Carolina at Chapel Hill) - Cancelled
Feb. 14
Jun Zhuang (UB Industrial and Systems Engineering)
Title: Applied Mathematics, Game Theory and Disaster Management
Abstract: Society is faced with a growing amount of property damage and casualties from man-made and natural disasters. Developing societal resilience to those disasters is critical but challenging. In particular, societal resilience is jointly determined by federal and local governments, private and non-profit sectors, and private citizens. We will present a sequence of applied mathematical game models among players such as federal, local, and foreign governments, private citizens, and adaptive adversaries. In particular, the governments and private citizens seek to protect lives, property, and critical infrastructure from both adaptive terrorists and non-adaptive natural disasters. The federal government can provide grants to local governments and foreign aid to foreign governments to protect against both natural and man-made disasters; and all levels of government can provide pre-disaster preparation and post-disaster relief to private citizens. Private citizens can also, of course, make their own investments. The tradeoffs between protecting against man-made and natural disasters, specifically between preparedness and relief, efficiency and equity, and between private and public investment, will be discussed.
Feb 21 Kazuo Yamazaki (University of Rochester)
Title: Global stability and uniform persistence of the reaction-convection-diffusion cholera epidemic model
Abstract: This talk concerns the speaker's collaborative work with Prof. Xueying Wang of Washington State University. Cholera is an infectious disease caused by the bacterium Vibrio cholerae. Its spread and consequence in countries of Africa, Southeast Asia, Haiti and central Mexico are well-known and indicates the need for an efficient mathematical model to control the spread of such a disease. In dynamics of population biology, an important disease threshold is called the basic reproduction number R0, which measures the expected number of secondary infections caused by one infectious individual during its infectious period in an otherwise susceptible population. In this talk, we discuss our recent result which showed that R0 serves as a parameter that predicts whether cholera will persist or become globally extinct. Specifically, when R0 is beneath one, the disease-free-equilibrium is globally attractive while if it exceeds one, then in the case the infectious hosts or the concentration of bacteria in the contaminated water are not initially identically zero, the uniform persistence can be proven as well as the existence of an endemic equilibrium. We also make remarks on previous results on similar models (e.g. malaria, dengue fever, avian influenza) and discuss remaining difficult open problems.
Feb 28 Matthew J. Hoffman (RIT)
- Cancelled
March 7 Sean Nixon (SUNY Geneseo)
Title: Parity-Time Symmetry in Optical Lattices
Abstract: Parity-Time-Symmetry gained notoriety as a way to extend quantum mechanics to non-Hermitian potentials. PT-symety allows for complex systems which still exhibit an all real spectrum (real energy levels in QM). Since then, the concept has been applied to optics, electronic circuits, Bose-Einstien condensates and other physical systems where a complex potential can be realized by adding gain and loss. In the presence of nonlinearity, these PT-symmetric systems exhibit phenomena which are incredibly rare in dissipative systems, including continuous families of solitons, stabilization nonlinear modes in unstable regimes, and unique evolution dynamics. And recently, the study of PT-symmetry has also involved searching for other complex systems with the same or similar properties.
March 14 Michael Langberg (UB Electrical Engineering) - Cancelled due to weather
Title: Can one network edge make a difference: The edge removal problem
Abstract: The "edge removal problem" addresses the loss in communication rate (i.e., capacity) when a single edge is removed from a given network. For example, one can ask whether removing a single cable of a given capacity C from the internet can have impact larger than C on the internet as a whole. Remarkably, this problem remains unsolved. That is, if we compare the capacity of a given network to the capacity of the same network after the removal of a single edge, it is currently unknown how much the network capacity can change. In this talk I will study the edge removal problem through the lens of reduction. Specifically, I will give an overview of several intriguing reductive connections that have emerged recently between the edge removal problem and seemingly unrelated problems in network communication.
(to be confirmed) Carina Curto (Penn State University)
Mar 28 Ferdinand Schweser (UB Department of Neurology)
Title: Mathematical Problems of the Quantification of Brain Tissue Composition and Integrity With Phase MRI
Abstract: The noninvasive tomographic quantification of physical properties of biological tissues has been a perpetual quest in the field of biomedical imaging. I will present recent developments toward this goal in the field of phase-based magnetic resonance imaging (MRI), a special variant of MRI that employs the phase of the complex-valued resonance signal. We have developed efficient direct and numerical methods to solve several inverse problems of computing magnetic and electric tissue properties from the tissues's interactions with the externally applied electromagnetic fields in the MRI scanner. These problems include large-scale 3D source separation and deconvolution problems.
I will begin the presentation with a brief introduction to the basics of MRI. We will then discuss some of the inverse problems and their practical relevance for biomedical imaging research and clinical routine. I will conclude with an overview of significant problems that remain unsolved.
April 4:
Matt Tranter (Loughborough University),
Department of Mathematical Sciences, Loughborough University,
Loughborough, LE11 3TU, UK
Title: Scattering of strain solitary waves in delaminated waveguides
Abstract:
In this talk I will discuss the dynamics of long longitudinal bulk strain solitary waves in
bonded elastic bars with delamination. We have developed direct and semi-analytical nu-
merical methods for these types of problems. The semi-analytical method is based on the
weakly nonlinear solution of the problem.
Firstly I will consider a symmetric perfectly bonded layered bar with delamination, showing
that the direct and semi-analytical results for the full scattering problem are in agreement.
Furthermore, ssion of an incident solitary wave can occur in the delaminated region of the
bar [1, 2]. The approach is extended to the case of a layered bar with a soft bonding layer,
described by a system of coupled Boussinesq equations supporting radiating solitary waves
[3]. The modelling indicates that a delamination of a given length can be detected by the
behaviour of the waves [4]. This is joint work with K. R. Khusnutdinova.
References
[1] K. R. Khusnutdinova, A. M. Samsonov, Fission of a longitudinal strain solitary wave in
a delaminated bar, Phys. Rev. E, 77 (2008) 066603.
[2] K. R. Khusnutdinova and M. R. Tranter, Modelling of nonlinear wave scattering in a
delaminated elastic bar, Proc. Roy. Soc. A, 471 (2015) 20150584.
[3] K. R. Khusnutdinova, A. M. Samsonov and A. S. Zakharov, Nonlinear layered lattice
model and generalized solitary waves in imperfectly bonded structures, Phys. Rev. E, 79
(2009) 056606.
[4] K. R. Khusnutdinova and M. R. Tranter, On radiating solitary waves in bi-layers with
delamination and coupled Ostrovsky equations, Chaos (in press) (2017).
April 6 James Boyle (UB) - This talk is on Thursday
Title: Horizon Annealing: A co-NP Problem in Creating an Ordinal Composite from Paleontological Data
Abstract: In the Earth's history there is an underlying true and unique sequence of appearances and extinctions of organisms because each organism arises only once and once extinct never reappears. If it were reliably known, scientists could use this ordered sequence of events as a proxy for time in their study of events in Earth history. However, the record of events is full of gaps and biases that obscure and mislead. What we are left with in the fossil record is a set of incomplete, fractured, and sometimes contradictory, local collections of fossil specimens. In order to try and estimate the true, or at least most consistent, order of events in Earth history more accurately, geologists have developed several quantitative methods by which to extract useful information from these imperfect data.
The Horizon Annealing (HA) approach that we employ to order events uses data collected from measured columns of layered rock at particular geographic sites where the order of occurrences within each layer is known. These are known as local sections. Typically, older rocks are found at the bottom of a column because they were laid down first. Older specimens appear lower in local sections, younger specimens at the top. However, each section does not have the complete range of all species. Many are missing and most are truncated, so the local range is less than, or at most equal to, the global range of a species.
In the HA process, the individual collections from each measured section are allowed to shuffle up and down at random relative to those in other sections, while preserving their internal orders. Occurrences from all of the collections are then combined to form a global ordering of events that minimizes the number of gaps within an organism's span of the composite sequence. Data sets often consist of several hundred sections, each containing tens of samples that record the presence of one or more of the several hundred species that existed during the interval examined. The data are often very noisy and the number of possible solutions scales exponentially with the size of the dataset. The solution space is expected to be complex and there are likely to be multiple equally optimal solutions for even modest datasets. Despite the difficulty in knowing whether the true answer has been found, a proposed solution can easily be rejected if its calculated score is higher than the best solution known, making this a co-NP problem. Nonetheless, it can be difficult to avoid having searches become trapped in a local minimum by particularly large or densely sampled local sections that were placed unfortunately in initial runs.
As we cannot be certain whether a solution is the true solution, measures of uncertainty are desirable. We have developed jackknife approach in which one local section is removed at a time, and a new solution is found. The relative movement of collections among successive jackknifed solutions serves as a proxy for uncertainty in placement. This process is time-consuming, computationally expensive, and suffers the same pitfalls as for the general HA search, noted above. As datasets have become increasingly large, the current implementation of HA becomes unworkable and more efficient algorithms or approaches are needed.
April 18
Yang Yang (Michigan Tech)
Title: Local discontinuous Galerkin methods for chemotaxis model
Abstract: In this talk, we will focus on local discontinuous Galerkin methods for
Keller-Segel chemotaxis model, which might yield blow-up solutions. We first give the
error estimates based on two different finite element spaces, and then
proceed to the positivity-preserving technique to obtain positive numerical
approximations. Finally, we will numerically demonstrate how to find the
blow-up time.
April 25 Antonio Moro (Northumbria University)
Title: Dressing networks: towards an integrability approach to collective and complex phenomena
Abstract: A large variety of real world systems can be naturally modelled by networks, i.e. graphs whose nodes represent the components of a system linked (interacting) according to specific statistical rules. A network is realised by a graph typically constituted by a large number of nodes/links. Fluid and magnetic models in Physics are just two among the many classical examples of systems which can be modelled by using simple or complex networks. In particular "extreme" conditions (thermodynamic regime), networks, just like fluids and magnets, exhibit a critical collective behaviour intended as a drastic change of state due to a continuous change of thermodynamic parameters.
Using an approach to thermodynamics, recently introduced to describe a general class of van der Waals type models and magnetic systems in mean field approximation, we analyse the integrable structure of corresponding networks and use the theory of nonlinear conservation laws to provide an analytical description of the system outside and inside the critical region.
April 27 Michael Langberg (UB Electrical Engineering) - This talk is on Thursday.
Title: Can one network edge make a difference: The edge removal problem
Abstract: The "edge removal problem" addresses the loss in communication rate (i.e., capacity) when a single edge is removed from a given network. For example, one can ask whether removing a single cable of a given capacity C from the internet can have impact larger than C on the internet as a whole. Remarkably, this problem remains unsolved. That is, if we compare the capacity of a given network to the capacity of the same network after the removal of a single edge, it is currently unknown how much the network capacity can change. In this talk I will study the edge removal problem through the lens of reduction. Specifically, I will give an overview of several intriguing reductive connections that have emerged recently between the edge removal problem and seemingly unrelated problems in network communication.
May 2 Ming Yan (Michigan State University)
Title: A New Primal-dual Operator Splitting Scheme and its Applications
Abstract: In this talk, I will introduce a new primal-dual algorithm for minimizing f(x) + g(x) + h(Ax), where f, g, and h are convex functions, f is differentiable with a Lipschitz continuous gradient, and A is a bounded linear operator. This new algorithm has the Chambolle-Pock and many other algorithms as special cases. It also enjoys most advantages of existing algorithms for solving the same problem. Then I will show some applications including fused lasso, image processing, and decentralized consensus optimization.
May 9 Kanika Bansal (UB Math)
Title: Data-driven models of brain dynamics to predict cognitive performances
Abstract: Humans show individual differences in cognitive performance and the origin of this variability is not completely understood. How important is the basic structural skeleton of the brain in explaining and predicting individual differences in cognition?
In this talk, I will discuss our work with a data-driven computational brain network model. By emphasizing differences in the underlying structural connectivity, this model serves as a powerful tool to differentiate individual performances in cognitively demanding tasks.
Motivated by experimental data on three language related tasks, we perform computational experiments in which we stimulate the left inferior frontal gyrus and quantify the spread of the stimulation both within the global brain network and throughout the task specific sub-networks
across a cohort of individuals. We then relate the patterns of activation to individual performance across three tasks and find that task performance correlates with the activation of either local or global circuitry depending on the complexity of the task.
(to be confirmed) Joint seminar with UB SIAM Student Chapter