TSVP Talk: "Mathematical Modelling Across Scales: From Microscopic to Macroscopic" by Havva Yoldas

Title: Mathematical Modelling Across Scales: From Microscopic to Macroscopic

Abstract: In this talk, I will present examples of constructing mathematical models for the same natural phenomenon at different time/space scales, particularly at microscopic, mesoscopic, and macroscopic levels. In the case of fluids, this hierarchy of scales begins with Newton's laws of motion, passes through the Boltzmann equation, and reaches up to fluid equations such as the Euler or Navier-Stokes equations. At each stage of this connection, I will discuss which type of questions mathematicians aim to answer. I will then focus more on the mesoscopic and macroscopic scales, providing examples of mathematical models from my research area. Specifically, I will discuss run-and-tumble models for chemotactic bacteria and differential equations used in modelling structured populations, such as neuron populations and selection-mutation processes.

Profile: Havva Yoldaş is an assistant professor at the Delft Institute of Applied Mathematics, TU Delft in the Netherlands. Her research focuses on analysis of partial differential equations (PDEs) arising from applied sciences. She is particularly interested in well-posedness and long-time behaviour of PDEs appearing in structured population dynamics (neuron population models, growth-fragmentation equations etc.), kinetic theory (Boltzmann-type equations, run and tumble equations for bacterial chemotaxis) and coupled PDE models such as cross-diffusion systems for competing species. Personal website

Language: English, no interpretation.

Target audience: General audience / everyone at OIST and beyond.
Freely accessible to all OIST members and guests without registration.

This talk will also be broadcast online via Zoom:

Meeting ID:930 2515 6556
Passcode:641557

※ Please note that this event may be recorded and the videos uploaded. In addition, photos may be taken during the event. These are intended for publication online (the OIST website, social media, etc.)※