معرفی
Irina Pettersson is an Associate Professor in Applied Mathematics and Statistics at Chalmers University of Technology. Her research focuses on asymptotic analysis and homogenization of differential equations, with applications in mathematical physics including electromagnetic scattering in materials with small particles and heat conduction.
In classical homogenization theory, she studies mixtures of materials with different properties that have two scales: a microscopic scale describing the microstructure of heterogeneous materials and a macroscopic scale. Homogenization theory provides methods to replace heterogeneous materials with homogeneous ones, making the equations easier to solve. A well-known example is the derivation of Darcy's law from the Navier-Stokes equations for transport in porous materials. Recently, Pettersson has been particularly interested in the derivation of cable equations for nerve fibers, which involves approximating 3D models with 1D models.
Her publication record shows a clear progression from traditional homogenization applications toward neuroscience-focused research, with recent papers examining nerve bundles, myelinated axons, and signal propagation in neurons. This interdisciplinary work connects mathematical theory with biological applications, demonstrating significant methodological innovation in multiscale modeling approaches.
She has received research funding from STINT (The Swedish Foundation for International Cooperation in Research and Higher Education) for the project 'EINervio - Modeling of ephaptic coupling of myelinated neurons' (2020-2022), which produced multiple publications. Her collaborative work appears in top-tier journals including SIAM Journal on Mathematical Analysis and SIAM Journal of Scientific Computing, indicating strong recognition within the mathematical community.
Pettersson's research program bridges theoretical mathematics with practical applications across multiple domains, demonstrating how rigorous mathematical frameworks can advance understanding of complex physical and biological phenomena. Her current work continues to expand the boundaries of homogenization theory while addressing challenging problems in neuroscience modeling.
