Workshops

MARS workshops

We are committed to turning mathematical research into solutions that tackle real-world challenges. Achieving this requires collaboration across disciplines, bringing together expertise from academia, industry, and government.

Our workshops, which are part- or whole-funded by our Research England grant, are designed to:

Foster interdisciplinary collaborations with researchers, focusing on our four main application areas.
Connect experts from different fields to explore innovative approaches to complex research challenges.
Engage non-academic partners to ensure we maximise the potential for translation into tangible impact.

Past workshops

Insights into Cell-Tissue Interactions via Mathematical Modelling (September 2026)

This workshop brought together researchers in various fields with an interest in cell-tissue interactions, particularly how to use mathematical modelling to further understand the subject.

The presentations included work in both mathematics and biology with the applications ranging from keloid, burn injury, glioblastoma, muscle injury, pigmentation patterns, Dupuytren disorders, cell cycle, and ageing effects.

This workshop was jointly funded by the and the School of Mathematical Sciences.

Organiser: Alice Peng (向日葵视频)

Outcomes: Upcoming and continuing collaborations between participants.

Data-Driven Modelling of Metallic Materials Across Scales (May 2026)

This Data Science and AI Institute (DSAIL) and MARS funded workshop brought together researchers in mathematics, engineering, chemistry, and materials science, along with industrial and national-lab partners, to explore how data and mathematics can bridge scales in modelling metals - from molecular dynamics to microstructure evolution and large-scale forming.

The event took place at Lancaster Castle in the historic city of Lancaster and featured invited talks, open discussions, and networking opportunities across the UK materials modelling community. It was open to all researchers with an interest in data-driven modelling of metallic materials.

Organisers: Maciej Buze (Lancaster) · (Warwick) · Wei Wen (Lancaster)

Outcomes: New interdisciplinary collaborations, strengthened networks, and foundational work to support a future grant proposal.

CoMPASs: Computational Materials Science and Mathematics at the Particle and Atomistic Scales (November 2025)

The goal of this workshop was to bring together researchers in computational materials science and mathematics to discuss mathematical models and algorithms essential for understanding and simulating materials at the atomic, molecular, and particle scales.

Set against the backdrop of emerging high-performance computational resources, such as the UK’s forthcoming first exascale supercomputer to be sited in Edinburgh, the workshop focused on the development of new mathematical and algorithmic methodologies which aimed to make the most of the computational power of future computer architectures in materials simulation. The workshop offered the opportunity for mathematicians to learn more about the new challenges and opportunities these computational platforms could bring.

Topics discussed included novel approaches to computational multi-tasking and sampling; optimisation methodologies such as numerical continuation and deflation; coarse-graining and model reduction; and the rigorous mathematical analysis of such methodologies.

Organisers: Maciej Buze (Lancaster) · (Warwick) · (University of North Carolina) · Danny Perez (Los Alamos National Laboratory)

Outcomes: Research collaborations between researchers from the UK, EU and US.

AI for Adaptive Environmental Decision-Making (June 2025)

Bringing together UK and international academics from computer science, economics, and environmental science, alongside practitioners from organisations such as the Environment Agency and JBA, this workshop explored how AI can support smarter, more adaptive responses to environmental risk. The discussions connected real-world challenges with cutting-edge research in modelling, optimisation and decision support.

Outcomes: New research collaborations and a co-authored working paper capturing key insights from the workshop and outlining priorities for future work.

This workshop was co-funded by Data Science and AI Institute (DSAIL) and MARS.

Mathematics, AI and Data Science for Material Innovations (June 2025)

This interdisciplinary workshop showcased emerging advances in the mathematical and scientific foundations of materials innovation, drawing participants from across the UK and internationally. The event provided a platform for PhD students and early-career researchers to present their work, helping to build a new community at the forefront of materials research.

Outcomes: Fresh collaborative initiatives, strengthened links between Lancaster researchers and colleagues at other institutions, and foundational work to support future large-scale grant proposals.

This workshop was co-funded by Data Science and AI Institute (DSAIL) and MARS.

Group of academics standing in front of a hill

Mathematics in the Life Sciences (May 2025)

This workshop, funded by MARS, convened researchers from across the life sciences to explore how mathematical methods and AI can drive discovery in fields ranging from biology and chemistry to environmental science, medicine and physics. Participants shared challenges, exchanged tools and approaches, and identified where quantitative methods could meaningfully accelerate progress.

Outcomes: New interdisciplinary collaborations, a shared plan for future joint research, and the launch of an externally funded follow-up workshop on AI for Ecology.

Probabilistic Programming Day (September 2024)

Part of the Isaac Newton Institute’s Modelling and Inference for Pandemic Preparedness (MIP) programme, this workshop, co-funded and co-organised by MARS, brought together an international community of researchers working at the intersection of pandemic preparedness, probabilistic methods, and outbreak data analysis. It offered a rare opportunity for experts to reconnect in person after COVID and exchange emerging ideas in epidemic modelling.

Outcomes: New research collaborations, strengthened international networks, and plans for follow-up meetings to refine and share the insights developed during the MIP programme.

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