RESEARCH TALKS

Olivier Bahn (HEC Montréal)

Integrated Assessment Modeling of Emerging Challenges: The Case of Climate Change

Abstract

To assess the potential long-term evolution of climate, it is essential to compute how anthropogenic greenhouse gas (GHG) emissions may change over time on a global scale. This requires an evaluation of the various drivers of GHG emissions, including demographic, economic, and technological factors. An integrated assessment approach combines these socio-economic elements with geophysical and environmental considerations, often employing computer-based integrated assessment models (IAMs). These models not only help evaluate future GHG emissions but also assess climate strategies, such as mitigation and adaptation options, and their impacts on climate change and associated damages. In this presentation, I will particularly focus on the development of the AD-MERGE 2.0 IAM at GERAD.

Morgan Craig (Université de Montréal)

Drivers of heterogeneous age-related immune kinetics after COVID-19 vaccination

Abstract

Mass COVID-19 vaccination campaigns shed light on how individual-level heterogeneity in vaccine responses affects population-level protection against pathogens. Age was seen to be highly correlated to mRNA COVID-19 vaccine efficacy, with older adults exhibiting generally weaker vaccine-elicited outcomes than younger individuals. However, this differential effect was shown to be reduced after the priming phase, with seniors “catching up” to the humoral responses of younger individuals. The immunological mechanisms driving these variable outcomes remain to be elucidated. Their identification would help to improve vaccination strategies and pinpoint characteristics predictive of strong immunity following prime-boost vaccination.

To gain insight into the spectrum of immune responses stimulated by mRNA COVID-19 vaccines, we constructed a mathematical model that comprehensively describes the development of immunological memory after vaccination. We extensively calibrated our model to clinical trial data from younger healthcare workers and older individuals. Our model’s predictions suggest that seniors exhibit weaker CD4+ T helper cell responses with accelerated clearance kinetics that contribute to overall weaker vaccine-induced antibody responses. This result has important implications for annual COVID-19 vaccination campaigns and public health planning.

Guillaume Dumas (Université de Montréal)

Modeling Complex Dynamics in Biological, Artificial, and Social Systems

Abstract

This talk presents an interdisciplinary approach to modeling complex dynamics in biological, artificial, and social systems. By integrating social cognitive neuroscience, dynamical systems theory, and scientific machine learning, we explore emergent behaviors in both natural and artificial neural networks, as well as in social interactions in humans and machines. Novel architectures are introduced to identify latent representations and capture critical transitions, offering new insights into cognitive processes and innovative tools for multi-agent coordination. Applications extend across cognitive neuroscience, healthcare, and climate action.

Andrew Granville (Université de Montréal)

Reasoning and creativity in mathematics and AI AI

Abstract

When AI appears to give more than it was programmed for, how should we interpret this? Has the AI been “reasoning”? Can the AI be “creative”? Perhaps one should ask first what those words really mean, whether they fit what AI is doing, or whether these concepts need to be interpreted differently?

Frédéric Guichard (McGill University)

Anticipating ecological tipping points under ongoing environmental change

Abstract

Ongoing climate change challenges current mathematical and computational approaches to the study of ecosystems as dynamic and coupled systems. In particular, the nonlinear response of species and whole ecosystems to their environment combined with accelerating changes in the global climate make the study of tipping points leading to catastrophic shifts in ecosystem health one of the hardest problems in ecology. I will first summarize standard approaches to the early detection of tipping points in ecology, including recent applications of deep l