M. Ram Murty (Queen's University)

Date

Monday January 15, 2024
3:00 pm - 4:00 pm

Location

Jeffery Hall, Room 319

Number Theory Seminar

Monday, January 15th, 2024

Time: 3:00 p.m.  Place: Jeffery Hall, Room 319

Speaker: M. Ram Murty (Queen's University)

Title: LINEAR RELATIONS AMONG SPECIAL VALUES OF THE DIGAMMA FUNCTION

Abstract: The digamma function is the logarithmic derivative of the gamma function and its special values appear in the evaluation of periodic L-series. I will discuss some recent joint work with Abhishek Bharadwaj and Siddhi Pathak in this context.

Weijing Tang (CMU)

Date

Friday January 12, 2024
2:30 pm - 3:30 pm

Location

Jeffery Hall, Room 234

Math & Stats Department Colloquium

Friday, January 12th, 2023

Time: 2:30 p.m.  Place: Jeffery Hall, Room 234

Speaker: Weijing Tang (CMU)

Title: Survival Analysis via Ordinary Differential Equations

Abstract: Survival analysis is an extensively studied branch of statistics with wide applications in various fields. Despite rich literature on survival analysis, the growing scale and complexity of modern data create new challenges that existing statistical models and estimation methods cannot meet. In the first part of this talk, I will introduce a novel and unified ordinary differential equation (ODE) framework for survival analysis. I will show that this ODE framework allows flexible modeling and enables a computationally and statistically efficient procedure for estimation and inference. In particular, the proposed estimation procedure is scalable, easy-to-implement, and applicable to a wide range of survival models. In the second part, I will present how the proposed ODE framework can be used to address the intrinsic optimization challenge in deep learning survival analysis, so as to accommodate data in diverse formats.

Bio: Weijing Tang is an Assistant Professor in the Department of Statistics and Data Science at Carnegie Mellon University. Her research interests include statistical network analysis, machine learning, and survival analysis with applications to health and social sciences. She has received multiple awards for her research work, including the ASA Nonparametric Statistics, Statistical Learning and Data Science, and ENAR Distinguished Student Paper Awards. Prior to CMU, she was a Postdoctoral Researcher at Harvard University. She received her Ph.D. from the University of Michigan and a B.Sc. from Tsinghua University.

 

Alexandre (Sasha) Zotine

Date

Thursday November 30, 2023
4:00 pm - 5:00 pm

Location

Jeffery Hall, Room 102

Curves Seminar

Thursday, November 30th, 2023

Time: 4:00 p.m.  Place: Jeffery Hall, Room 102

Speaker: Alexandre (Sasha) Zotine

Title: Classifying Cluster Algebras of Finite Type

Abstract: We'll shift gears by beginning to discuss the classification of cluster algebras of finite type. In this talk, we'll particularly consider the rank one and two cases, which will involve more explicit calculations.

Zihang Lu (Queen’s)

Date

Friday December 1, 2023
2:30 pm - 3:30 pm

Location

Jeffery Hall, Room 234

Math & Stats Department Colloquium

Friday, December 1st, 2023

Time: 2:30 p.m.  Place: Jeffery Hall, Room 234

Speaker: Zihang Lu (Queen’s)

Title: Integrating Multidimensional Longitudinal Features to Discover Disease Phenotypes: A Bayesian Consensus Clustering Approach

Abstract: Clustering longitudinal features is a common research goal in health studies to identify distinct developmental patterns that reflect disease phenotypes and to facilitate targeted intervention. Compared to clustering a single longitudinal feature, integrating multiple longitudinal features allows additional information to be incorporated into the clustering process, which reveals co-existing developmental patterns and generates deeper biological insight. In this talk, I will discuss a newly developed Bayesian clustering approach for clustering multidimensional and high-dimensional longitudinal features with complex data structures. Results from analyzing birth cohort data to discover respiratory phenotypes will be presented and discussed.

Bio: Dr. Zihang Lu is an Assistant Professor in the Department of Public Health Sciences at Queen’s University, with a cross-appointment to the Department of Mathematics and Statistics. He completed an MSc and PhD in Biostatistics from the University of Toronto. Dr. Lu’s research focuses on statistical and machine learning methods motivated by high-dimensional and large health data with complex structures. His research is supported by funding from the Natural Sciences and Engineering Research Council of Canada and the Canadian Institutes of Health Research.

 

Chi Cheuk Tsang (UQAM)

Date

Monday November 27, 2023
11:00 am - 12:00 pm

Location

Jeffery Hall, Room 319

Dynamics, Geometry and Groups Seminar

Monday, November 27th, 2023

Time: 11:00 a.m.  Place: Jeffery Hall, Room 319

Speaker: Chi Cheuk Tsang (UQAM)

Title: Birkhoff sections for Anosov flows

Abstract: A global section to a flow on a 3-manifold is a closed cooriented embedded surface that is positively transverse to the flow lines. A Birkhoff section is a generalization where one allows the surface to admit boundary components tangent to the flow. Using Birkhoff sections, one can convert between dynamical information of 3-dimensional flows and 2-dimensional maps. A classical result of Fried states that every transitive Anosov flow admits a Birkhoff section. The natural next question is how simple of a Birkhoff section can we find. In this talk, we discuss some recent progress on this question. If time permits, we will also explain some tools and ideas used in the proofs of the results that we mention.

Luke Steverango

Date

Thursday November 23, 2023
4:00 pm - 5:00 pm

Location

Jeffery Hall, Room 102

Curves Seminar

Thursday, November 23rd, 2023

Time: 4:00 p.m.  Place: Jeffery Hall, Room 102

Speaker: Luke Steverango

Title: Tropical Semifields and Seed Patterns

Abstract: In this talk, we will examine another way of encoding the data we have used previously, specifically focusing on how to encode the data from the frozen variables in our extended exchange matrix. In this case, we introduce the tropical semifield and will express the exchange relations in terms of a new operation called tropical addition. The advantage of this new framework is that it allows us to perform calculations for arbitrary extensions of a given exchange matrix.

Grayson Plumpton (Queen's University)

Date

Tuesday November 21, 2023
4:00 pm - 5:00 pm

Location

Jeffery Hall, Room 319

Number Theory Seminar

Tuesday, November 21st, 2023

Time: 4:00 p.m.  Place: Jeffery Hall, Room 319

Speaker: Grayson Plumpton (Queen's University)

Title: Some probability laws concerning the Dedekind zeta functions of $\mathbb{Q}$, $\mathbb{Q}(\sqrt{-1})$ and $\mathbb{Q}(\sqrt{-2})$.

Abstract: This talk is a follow up to a talk given at the number theory seminar in winter 2023, in which we introduce the paper “Probability laws related to the Jacobi theta and Riemann zeta functions, and Brownian excursions” by Phillipe Biane, Jim Pitman, and Marc Yor. In this talk, we will reframe some ideas from this paper using the language of Tate-Iwasawa theory, and use this to give a probabilistic interpretation of the Dedekind zeta functions of the fields $\mathbb{Q}$, $\mathbb{Q}(\sqrt{-1})$ and $\mathbb{Q}(\sqrt{-2})$.

Felicia Magpantay (Queen’s University)

Date

Friday November 17, 2023
2:30 pm - 3:30 pm

Location

Jeffery Hall, Room 234

Math & Stats Department Colloquium

Felicia Magpantay (Queen’s University)

Friday, November 17th, 2023

Time: 2:30 p.m.  Place: Jeffery Hall, Room 234

Speaker: Felicia Magpantay (Queen’s University)

Title: Challenges in modeling the transmission dynamics of childhood diseases

Abstract: Mathematical models of childhood diseases are often fitted using deterministic methods under the assumption of homogeneous contact rates within populations. Such models can provide good agreement with data in the absence of significant changes in population demography or transmission, such as in the case of pre-vaccine era measles. However, accurate modeling and forecasting after the start of mass vaccination have proven to be more challenging. This is true even in the case of measles which has a well understood natural history and a very effective vaccine. We demonstrate how the dynamics of homogeneous and age-structured models can be similar in the absence of vaccination, but diverge after vaccine roll-out. We also present the different methods used to fit deterministic and stochastic models, and propose new techniques to fit long term time series with imperfect covariate information. The methods we develop can be applied to many types of complex systems beyond those in disease ecology.

Bio: Prof. Felicia Magpantay is an Associate Professor here at Queen’s, working in the fields of mathematical modeling and biomathematics, as well as differential equations, applied dynamics and applied probability. Prof. Magpantay obtained her Ph.D. in 2012 from McGill, then held postdoctoral positions at York University and the University of Michigan, and an assistant professor position at the University of Manitoba before joining Queen’s in 2017.

 

Calvin Fletcher

Date

Thursday November 16, 2023
4:00 pm - 5:00 pm

Location

Jeffery Hall, Room 102

Curves Seminar

Thursday, November 16th, 2023

Time: 4:00 p.m.  Place: Jeffery Hall, Room 102

Speaker: Sonja Ruzic

Title: Y-patterns: Motivation and examples

Abstract: Last week we were briefly introduced to Y-patterns. In this talk, we will study Y-patterns more extensively and seek to understand why they are important, both as an independent object of study but also in comparison to ordinary patterns. In order to help motivate Y-patterns further, we will study several examples.

V. Kumar Murty (Fields Institute and U of T)

Date

Tuesday November 14, 2023
3:30 pm - 4:30 pm

Location

Jeffery Hall, Room 102

Number Theory Seminar

Tuesday, November 14th, 2023

Time: 3:30 p.m.  Place: Jeffery Hall, Room 102

Speaker: V. Kumar Murty (Fields Institute and U of T)

Title: Pair correlation and the Chebotarev density theorem

Abstract: We describe a pair correlation hypothesis for Artin L-functions and discuss the implications for the error term in the Chebotarev density theorem. We then discuss what can be proved about the hypothesis itself.