Department of Mathematics and Statistics

Department of Mathematics and Statistics
Department of Mathematics and Statistics
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Department Colloquium

Department Colloquium - Milen Yakimov (Northeastern University)

Milen Yakimov (Northeastern University)

Friday, January 29th, 2021

Time: 2:30 p.m.  Place: Online (via Zoom)

Speaker: Milen Yakimov (Northeastern University)

Title: Noncommutative Discriminants.

Abstract: The notion of discriminant plays an important role in various algebraic, geometric and combinatorial settings. The discriminant of a noncommutative algebra is modeled on Dedekind's definition for algebraic number fields. The discriminants in the former class have many applications but have only been computed in few situations. We will present an introduction to this subject and will then describe three general theorems for computing discriminants of noncommutative algebras based on Poisson geometry, Representation Theory and Cluster Algebras, respectively. The three theorems can be applied to compute the discriminants of many families of algebras of wide interest: quantum matrices at roots of unity, quantum Weyl algebras, quantum Schubert cell algebras, algebras in noncommutative projective algebraic geometry and others. The talk is based on joint work with Kenneth Brown (Glasgow University), Bach Nguyen (Xavier University) and Kurt Trampel (University of Notre Dame).

Milen Yakimov is a Professor in the Department of Mathematics at Northeastern University. His research interests include noncommutative algebra, quantum groups, Poisson geometry, cluster algebras, representation theory and integrable systems. Before joining Northeastern University, he was the Michael F. and Roberta Nesbit McDonald Professor in the Department of Mathematics at the Louisiana State University. He became a Fellow of the American Mathematical Society in 2018.

Department Colloquium - Mohammad Farazmand (NC State)

Mohammad Farazmand (NC State University)

Friday, January 22nd, 2021

Time: 2:30 p.m.  Place: Online (via Zoom)

Speaker: Mohammad Farazmand (NC State University)

Title: Extreme Events: Dynamics, Prediction and Mitigation.

Abstract: A wide range of natural and engineering systems exhibit extreme events, i.e., spontaneous intermittent behavior manifested through sporadic bursts in the time series of their observables. Examples include ocean rogue waves, intermittency in turbulence, extreme weather patterns and epileptic seizure. Because of their undesirable impact on the system or the surrounding environment, the real-time prediction and mitigation of extreme events is of great interest. In this talk, I will discuss three aspects of extreme events. First, I introduce a variational method that unveils the mechanisms underpinning the formation of extreme events. Next, I show how this framework enables the data-driven, real-time prediction of extreme events. I demonstrate the application of this method with several examples, including the prediction of ocean rogue waves and the intermittent energy dissipation bursts in turbulent fluid flows. Finally, I will discuss a closed-loop adaptive control and a delay feedback control for mitigating extreme events.

Mohammad Farazmand is an assistant professor within the Department of Mathematics at North Carolina State University. He works on the fields of data-driven modeling and analysis of complex systems. He was previously a postdoctoral associate at the Massachusetts Institute of Technology and a J. Ford Postdoctoral Fellow at the Georgia Institute of Technology. He obtained his Ph.D. in 2014 from ETH Zurich under the supervision of George Haller.

Department Colloquium - Grace Y. Yi (University of Western Ontario)

Grace Y. Yi (University of Western Ontario)

Friday, January 15th, 2021

Time: 2:30 p.m.  Place: Online (via Zoom)

Speaker: Grace Y. Yi (University of Western Ontario)

Title: Characterizing the Dynamic of COVID-19 with a New Epidemic Model.

Abstract: The mystery of the coronavirus disease 2019 (COVID-19) and the lack of effective treatment for COVID-19 have presented a strikingly negative impact on public health. While research on COVID-19 has been ramping up rapidly, a very important yet somewhat overlooked challenge is on the quality and unique features of COVID-19 data. The manifestations of COVID-19 are not yet well understood. The swift spread of the virus is largely attributed to its stealthy transmissions in which infected patients may be asymptomatic or exhibit only flu-like symptoms in the early stage. Due to the limited test resources and a good portion of asymptomatic infections, the confirmed cases are typically under-reported, error-contaminated, and involved with substantial noise. In this talk, I will discuss some issues related to faulty COVID-19 data and present a new model to describe the dynamic evolution of COVID-19. In addition, I will mention a website of COVID-19 Canada (, developed by the team co-led by Dr. Wenqing He and myself, which provides a comprehensive and real-time visualization of the Canadian COVID-19 data.

Grace Y. Yi is a professor of the University of Western Ontario where she currently holds a Tier I Canada Research Chair in Data Science. She received her Ph.D. in Statistics from the University of Toronto in 2000 and then joined the University of Waterloo as a postdoctoral fellow (2000-2001), Assistant Professor (2001-2004), Associate Professor (2004-2010), Professor (2010-2019), and University Research Chair (2011-2018). Her research interests focus on developing methodology to address various challenges concerning Data Science, public health, cancer research, epidemiological studies, environmental studies, and social science. Her recent research has been centered around investigating machine learning and statistical methods to tackle problems concerning imaging data, missing data, measurement error in variables, causal inference, high dimensional data, survival data, and longitudinal data. She is a Fellow of the Institute of Mathematical Statistics, a Fellow of the American Statistical Association, and an Elected Member of the International Statistical Institute. She won the prestigious CRM–SSC Prize of the Statistical Society of Canada in 2010. She was a recipient of the University Faculty Award (2004-2009) granted by the Natural Sciences and Engineering Research Council of Canada. Her work with Xianming Tan and Runze Li won the Canadian Journal of Statistics Award for 2016. She has served the professions in various capacities. She was the Editor-in-Chief of The Canadian Journal of Statistics (2016-2018) as well as the President of the Biostatistics Section of the Statistical Society of Canada in 2016, and the Founder of the first chapter (Canada Chapter, established in 2012) of International Chinese Statistical Association (ICSA).

Department Colloquium - Ian Frankel (Queen's University)

Ian Frankel (Queen's University)

Friday, November 27th, 2020

Time: 2:30 p.m.  Place: Online (via Zoom)

Speaker: Ian Frankel (Queen's University)

Title: Invariant measures for straight line flows.

Abstract: We discuss the question of equidistribution of billiard trajectories in polygons. As it turns out, for polygons whose angles are rational, this is related to the geometry of a 1-parameter family of surfaces in a moduli space. We will describe how the possible measures with respect to which a billiard trajectory may equidistribute are constrained by this 1-parameter family of surfaces.

Ian Frankel is a Coleman Research Fellow within the Department of Mathematics and Statistics at Queen’s University. He obtained his Ph.D. in Mathematics from the University of Chicago in 2018. He was a Research Fellow at the Higher School of Economics and a Fields Postdoctoral Fellow at The Fields Institute for Research in Mathematical Sciences. He is mainly interested in geometry and topology and dynamical systems.

Department Colloquium - Nicolas Fraiman (U of North Carolina)

Nicolas Fraiman (University of North Carolina)

Friday, November 20th, 2020

Time: 2:30 p.m.  Place: Online (via Zoom)

Speaker: Nicolas Fraiman (University of North Carolina)

Title: Stochastic Recursions on Random Graphs.

Abstract: We study a family of Markov processes on directed graphs where the values at each vertex are influenced by the values of its inbound neighbors and by independent fluctuations either on the vertices themselves or on the edges connecting them to their inbound neighbors. Typical examples include PageRank and other information propagation processes. Assuming a stationary distribution exists for this Markov chain, our goal is to characterize the marginal distribution of a uniformly chosen vertex in the graph. In order to obtain a meaningful characterization, we assume that the underlying graph is either a directed configuration graph or an inhomogeneous random digraph, both of which are known to converge, in the local weak sense, to a marked Galton-Watson process. We prove that the stationary distribution on the graph converges in a Wasserstein metric to a function of i.i.d. copies of the special endogenous solution to a branching distributional fixed-point equation. This is joint work with Mariana Olvera-Cravioto and Tzu-Chi Lin.

Nicolas Fraiman is an Assistant Professor in the Department of Statistics and Operations Research at the University of North Carolina at Chapel Hill. He obtained his Ph.D. from McGill University in 2013. He was a Postdoctoral Fellow at the University of Pennsylvania and Harvard University. He works on the probabilistic analysis of random structures, stochastic dynamics, randomized algorithms and combinatorial statistics.

Department Colloquium - Yaiza Canzani (U of North Carolina)

Yaiza Canzani (University of North Carolina)

Friday, November 13th, 2020

Time: 2:30 p.m.  Place: Online (via Zoom)

Speaker: Yaiza Canzani (University of North Carolina)

Title: Eigenfunction concentration via geodesic beams.

Abstract: A vast array of physical phenomena, ranging from the propagation of waves to the location of quantum particles, is dictated by the behavior of Laplace eigenfunctions. Because of this, it is crucial to understand how various measures of eigenfunction concentration respond to the background dynamics of the geodesic flow. In collaboration with J. Galkowski, we developed a framework to approach this problem that hinges on decomposing eigenfunctions into geodesic beams. In this talk, I will present these techniques and explain how to use them to obtain quantitative improvements on the standard estimates for the eigenfunction's pointwise behavior, Lp norms, and for both pointwise and integrated Weyl Laws. One consequence of this method is a quantitatively improved Weyl Law for the eigenvalue counting function on all product manifolds.

Yaiza Canzani is an Assistant Professor in the Department of Mathematics at the University of North Carolina at Chapel Hill. She was awarded a Sloan Research Fellowship in 2018. Before joining UNC, Prof. Canzani was a Benjamin Peirce Fellow at Harvard University and a member of the Institute for Advanced Study. She obtained her Ph.D. from McGill University in 2013 under the supervision of Dmitry Jakobson and John Toth. She works on geometric analysis and spectral theory.

Department Colloquium - Florian Richter (Northwestern University)

Florian Richter (Northwestern University)

Friday, November 6th, 2020

Time: 2:30 p.m.  Place: Online (via Zoom)

Speaker: Florian Richter (Northwestern University)

Title: Dynamical generalizations of the Prime Number Theorem and disjointness of additive and multiplicative actions.

Abstract: One of the fundamental challenges in number theory is to understand the intricate way in which the additive and multiplicative structures in the integers intertwine. We will explore a dynamical approach to this topic. After introducing a new dynamical framework for treating questions in multiplicative number theory, we will present an ergodic theorem which contains various classical number-theoretic results, such as the Prime Number Theorem, as special cases. This naturally leads to a formulation of an extended form of Sarnak's Mobius randomness conjecture, which deals with the disjointness of actions of (N,+) and (N,*). This talk is based on joint work with Vitaly Bergelson.

Florian Richter is a Boas Assistant Professor in the Department of Mathematics at Northwestern University. He received his Ph.D. from The Ohio State University in 2018 under the supervision of Vitaly Bergelson. He received The Elizabeth Clay Howald Presidential Fellowship and Louise B.C. Vetter award for excellence in research from Ohio State. He works on dynamical systems, combniatorics and number theory.

Department Colloquium - Emine Yildirim (Queen’s University)

Emine Yildirim (Queen’s University)

Friday, October 23rd, 2020

Time: 2:30 p.m.  Place: Online (via Zoom)

Speaker: Emine Yildirim (Queen’s University)

Title: Graphs and Combinatorics in Representation Theory of Algebras.

Abstract: Representation theorists of finite dimensional algebras often use quivers, also known as directed graphs, and many other combinatorial tools associated with these quivers. This is because we understand the module category of algebras via representation of quivers. On the other hand, we also capture the beautiful combinatorics of cluster algebras via the same representation theory. In this talk, I will outline how this machinery works along with some recent results on Cluster Categories we obtained joint with Charles Paquette using the combinatorics and representations theory of quivers.

Emine Yildirim is a Coleman Research Fellow within the Department of Mathematics and Statistics at Queen’s University. She obtained her Ph.D. in Mathematics from the Universite du Quebec a Montreal in 2018. She is mainly interested in representation theory of algebras, specifically path algebras, incidence algebras, and their representations. She also works on cluster algebras, their categorification and related combinatorics.

Department Colloquium - Rafael Potrie (U de la Republica-Uruguay)

Rafael Potrie (Universidad de la Republica-Uruguay)

Friday, October 16th, 2020

Time: 2:30 p.m.  Place: Online (via Zoom)

Speaker: Rafael Potrie (Universidad de la Republica-Uruguay)

Title: Anosov flows and the fundamental group.

Abstract: The hairy ball theorem says that a vector field in the sphere must have some singularity. How does the dynamics interact with the topology of the underlying manifold in higher dimensions? We will discuss some instances of this question for dynamics in 3-manifolds, featuring a beautiful result due to Margulis and Plante-Thurston. Time permitting, we will touch upon more recent developments on the interactions between the topology and dynamics in 3 dimensions.

Rafael Potrie is an Associate Professor at the Universidad de la Republica-Uruguay. He obtained his Ph.D. in Mathematics from Universite Paris 13/Universidad de la Republica-Uruguay in 2012. He was an invited speaker of the Dynamical Systems session at the International Congress of Mathematicians (ICM) in 2018. His research mainly concerns the topological classification of partially hyperbolic systems in three-dimensional manifolds and its dynamical consequences. Other interests include smooth dynamics, ergodic theory, discrete subgroups of Lie groups, and the geometry of foliations and laminations.

Department Colloquium - Farouk Nathoo (University of Victoria)

Farouk Nathoo  (University of Victoria)

Friday, October 9th, 2020

Time: 2:30 p.m.  Place: Online (via Zoom)

Speaker: Farouk Nathoo (University of Victoria)

Title: Spatial Statistical Modeling for Neuroimaging Data.

Abstract: I will describe three projects involving the analysis of neuroimaging data and the development of hierarchical spatial Bayesian models for each. In the first, we develop an approach for determining the location and dynamics of brain activity from combined magnetoencephalography and electroencephalography data. The resulting inverse problem is ill-posed and we propose a distributed solution based on a Bayesian spatial finite mixture model that incorporates the Potts model to represent the spatial dependence in an allocation process that partitions the cortical surface into a small number of latent states. In the second project, we consider statistical modelling of functional magnetic resonance imaging (fMRI) data which is challenging in part as the data are both spatially and temporally correlated. Motivated by an event‐related fMRI experiment, we propose a novel hierarchical Bayesian model with automatic selection of the auto‐regressive orders of the noise process that vary spatially over the brain. In the third project, we develop a Bayesian bivariate spatial model for multivariate regression analysis applicable to studies examining the influence of genetic variation on brain structure. Our model is motivated by an imaging genetics study of the Alzheimer's Disease Neuroimaging Initiative, where the objective is to examine the association between images of volumetric and cortical thickness values summarizing the structure of the brain as measured by magnetic resonance imaging (MRI) and a set of 486 SNPs from 33 Alzheimer's Disease (AD) candidate genes obtained from 632 subjects. A bivariate spatial process model is developed to accommodate the correlation structures typically seen in structural brain imaging data and we develop a mean-field variational Bayes algorithm and a Gibbs sampling algorithm to fit the model. We compare the new spatial model to an existing non-spatial model in our motivating application.