Data Assimilation in Medical Models and Digital Twins One of the growing areas of interest in the context of biological and medical models is the question of how to personalize a model to a target organism or patient in order to improve model predictions. This question is inherently tied to data assimilation (DA): the process …
NPIs, vaccination, and collective action under social norms Social dynamics are an integral part of the spread of disease affecting contact rates as well as the adoption of pharmaceutical and non-pharmaceutical interventions (NPIs). This talk will present behavioural-epidemiological models that feature tipping-point dynamics for the uptake of vaccines or adoption of NPIs that combine the risk …
Discovering dynamical patterns of activity from single-trial intracranial EEG recordings In this talk I will discuss a data-driven method that leverages time-delayed coordinates, diffusion maps, and dynamic mode decomposition, to identify neural features in large scale brain recordings that correlate with subject-reported perception. The method captures the dynamics of perception at multiple timescales and distinguishes …
An approximate Bayesian computation approach for embryonic astrocyte migration model reduction During embryonic development of the retina of the eye, astrocytes, a type of glial cell, migrate over the retinal surface and form a dynamic mesh. This mesh then serves as scaffolding for blood vessels to form the retinal vasculature network that supplies oxygen and …
Image analysis and agent-based modeling of tumor-immune interactions in the glioblastoma microenvironment Glioblastoma is a highly aggressive and deadly brain cancer with no current treatment options available that can achieve remission. One potential explanation for minimally effective treatments is the ability of gliomas to take advantage of processes within the body's immune system to infiltrate …
My trajectory towards mathematical modeling of pulmonary infections The immune response to respiratory infections is highly complex and multiscale, making it amenable for mathematical modeling. Fungal respiratory infections are becoming increasingly prevalent and pose the threat of antimicrobial resistance. The immune response to respiratory pathogens is highly complex and multiscale, making it difficult to predict …
Novel Statistical Analysis Methods in Neuroimaging Using Diffusion MRI In this talk, I will discuss the fundamentals of diffusion MRI and explain how various features are extracted and their importance in neuroimaging analysis. I will then discuss some of the scientific applications and end with future possibilities.
Unveiling the Hidden Threat: The Impact of Sub-Optimum Treatment on Acquired Immunity, Asymptomatic Cases, Malaria Dynamics Malaria remains a persistent global health issue, despite ongoing control efforts such as anti-malarial drugs and insecticide-treated bed-nets, indoor residual spraying, etc.. The greatest impact of malaria, a mosquito-borne illness, is felt in Africa. This study develops a compartmental …
Reproducible Stochastic Simulation Stochastic simulations are commonly used to quantitatively or semi-quantitatively describe the dynamics of biological systems. At various scales and in multiple applications, stochastic simulation better reflects observed biological processes and robustness. Various methods are widely used to incorporate stochasticity into biological simulation, such as the Gillespie stochastic simulation algorithm for systems biology …
Uncertainty Quantification in Complex Models of Complicated Biology Validated mathematical models of complex biological phenomena are increasingly recognized as invaluable for elucidating mechanisms that underlie real-world (experimental or clinical) observations. Agent-based models (ABMs) have emerged as a natural formulation of choice in such models, providing a logical structure for capturing the multiple time and spatial …
