Prof. Bard Ermentrout
Title:
XPPAUT: A short historical perspective
Abstract:
In this talk, I will describe the evolution of the software program XPPAUT from its beginnings as a single equation simulator for a computational neuroscience course to its current version which runs on many platforms and has been used by thousands of researchers.
Dr Matthew England
Title:
Advancing computer algebra through other algorithmic domains
Abstract:
In this talk I will broadly describe the subfield of mathematics known as symbolic computation / computer algebra and the in particular my own special interest of cylindrical algebraic decomposition. I will describe how this subfield has made advances in recent years through interaction with other algorithmic domains: satisfiability checking and machine learning. The aim of the talk is to show how seemingly different areas of algorithms science may actually influence and advance each other, with the message that students would benefit from exploring widely and looking for connections.
Dr Anass Bouchnita
Title:
A genotype-structured epidemiological model to gain insights into the emergence and competition of variants
Abstract:
Genotype-structured models have been instrumental in unraveling the complexities of systems originating from ecology, immunology, and oncology. These models provide a continuous framework for integrating evolutionary mechanisms into population dynamics. Here, we introduce, for the first time, a phenotype-structured model applied to the study of infectious disease. It expands on previously developed susceptible-infected-recovered (SIR) model with population-immunity and describes virus evolution as a diffusion process. After calibrating the model, we apply it to show that a high basic reproduction rate, elevated mutation rate, broader cross-protection, and diminished genotypic distance are all factors that promote the emergence of variants. Moreover, we assess the impact of variant emergence based on the characteristics of the original and emerging variant, the robustness and broadness of population immunity, and the mutation rate. Our simulations underscore the necessity of broad cross-immunity for eradicating the original variant post-emergence of a more transmissible one. Furthermore, we demonstrate that robust, cross-variant immunity reduce the frequency of outbreaks driven by virus evolution and immune waning. This adaptable approach can be used to study a wide range of viruses and can be used to integrate genomic data into epidemiological modeling frameworks.
Dr Bao Tang
Title:
Chemical reaction network theory and Partial differential equations
Abstract:
Chemical reaction network theory (CRNT) generally studies dynamical behaviour of large chemical reaction systems relying on their network structure rather than explicit reaction rate constants. CRNT has been extensively studied in the spatially homogeneous setting, i.e. there is no spatial dependence and the problem under consideration is modelled by a system of ordinary differential equations. Realistically speaking, spatial heterogeneity needs to be taken into account, leading to the study of systems of partial differential equations. This talk identifies some key challenges in this setting and presents some recent results with their applications in molecular communications or game theory.
Dr Hong Duong
Title:
Evolution, Game Theory and Evolution of Cooperation
Abstract:
Evolutionary game theory, which incorporates game theory into Darwin’s evolution theory, constitutes a powerful mathematical framework for the study of dynamics of frequencies of competing strategies in large populations. Introduced in 1973 by Maynard Smith and Price in 1973, over the last 50 years, the theory has found its applications in diverse disciplines including biology, physics, economics, computer sciences and mathematics.
In this talk, I will give a short introduction to evolutionary game theory, and its applications in the study of evolution and promotion of cooperation.
Dr Alexandru Iosif
Title:
Sturm sequences and a discriminant in biology
Abstract:
In this talk we do a short introduction to computational real algebraic geometry through some classic results like the Descartes Rule of Signs, Sturm Theorem, and the more recent Tarski-Seidenberg Algorithm. We also show that these results can still be used in research by computing a discriminant of a system originated in biology.
Dr Abhishek Pal Majumder
Title:
Moneyball Revisited: Leveraging Data Analytics for Competitive Advantage in Baseball
Abstract:
In this presentation, we study the application of sabermetrics and its impact on baseball, focusing on the success story of the 2002 Oakland Athletics team. Through the lens of Michael Lewis's best-seller "Moneyball," we explore how using simple linear regression ideas, the Athletics identified undervalued talents and assembled a great team under financial constraints. We show how innovative thinking and data-driven decision-making can level the playing field for small-market teams and reshape the landscape of any professional sports. Join us as we unravel the timeless lessons of "Moneyball" and explore the enduring legacy of the Oakland Athletics' remarkable journey to success.
Dr Xiaolei Xie
Title:
Introduction to Stochastic Differential Equations in Finance
Abstract:
Stochastic Differential Equations (SDE) are widely used in the finance industry with their applications ranging from risk management to asset pricing. This talk will cover the basics of the topic and will give examples of its applications, including Value at Risk, Expected Shortfall, the Black-Scholes' formula, among others.
