UNIVERSITE DE MONTREAL

Their core work

Université de Montréal is a major Canadian research university that participates in European research through mobility and exchange programmes, contributing specialized expertise across a remarkably broad range of disciplines. Their researchers bring strengths in mathematical physics, machine learning, ecology, and humanities to European consortia — typically through MSCA individual fellowships and staff exchanges. As a non-EU partner, they provide transatlantic research links and access to Canada's deep AI and computational science ecosystem, particularly Montreal's globally recognized machine learning community.

What they specialise in

How they've shifted over time

In the early period (2015–2018), UdeM's H2020 involvement centred on fundamental science — quantum optics, polariton lasers, hybrid perovskites, integrable systems, and random matrices — reflecting their strength in mathematical and physical sciences. From 2019 onward, a clear shift emerged toward machine learning, generative neural networks, and data-driven modelling (STRUDEL, RISING), alongside large-scale environmental science (iAtlantic) and migration studies (Im.magine). This trajectory mirrors Montreal's rise as a global AI hub and shows the university increasingly bridging computational methods with applied domains.

UdeM is pivoting from fundamental physics toward AI-driven approaches across disciplines, making them an increasingly valuable partner for projects needing computational and machine learning expertise.

How they like to work

UdeM never coordinates H2020 projects — all 15 participations are as partner or third party, which is typical for non-EU institutions that cannot lead Horizon calls. With 95 unique partners across 28 countries, they operate as a wide-network contributor rather than a hub anchored to repeat collaborators. Their heavy use of MSCA fellowships (12 of 15 projects) indicates they primarily engage through individual researcher mobility rather than institutional-level commitments.

Broadly connected across 28 countries with 95 distinct consortium partners, reflecting the diversity of MSCA mobility schemes rather than concentrated strategic alliances. Their network spans Europe widely with no single geographic cluster.

What sets them apart

As a Canadian university, UdeM offers European consortia a transatlantic dimension and access to Montreal's world-class AI and deep learning ecosystem — home to MILA and some of the field's founders. Their disciplinary breadth (from quantum physics to humanities to marine science) is unusual, meaning they can supply specialist researchers across very different project types. For consortium builders, they are a reliable third-country partner who adds international reach without requiring coordination overhead.

Highlights from their portfolio

• iAtlantic
  Large-scale RIA integrating Atlantic marine ecosystem assessment across space and time — UdeM's biggest and most interdisciplinary H2020 involvement.
• STRUDEL
  Directly connects information theory with deep learning — positions UdeM at the intersection of Montreal's AI strengths and European research networks.
• IPaDEGAN
  Five-year MSCA-RISE network on integrable PDEs linking geometry, asymptotics, and numerics — their longest-running mathematical physics collaboration.