AI for Science Workshop — Showcasing AI Across Lancaster

Artificial intelligence is rapidly changing how we do science: how we collect data, build models, run experiments, design materials, interpret results, quantify uncertainty, and translate findings into real-world impact. This workshop brings together colleagues from across Lancaster to share practical examples of AI for Science—from early-stage ideas to mature projects—and to build connections that can turn good work into collaborative programmes and fundable bids.

Whether you want to learn what others are doing, stress-test an idea, find collaborators, or showcase your work, this is a structured, campus-wide forum focused specifically on the opportunities for scientific discovery with AI.

• Short, focused talks (10–15 minutes): Lightning-style presentations from academics, PDRAs and PhD students on how AI is enabling scientific research and discovery.
• What worked (and what didn’t): Each speaker will briefly cover (i) the core problem, (ii) the AI method(s) used, (iii) what was learned/achieved, and (iv) limitations—data issues, compute constraints, evaluation challenges, reproducibility, governance/ethics, etc.
• Poster + networking session (over lunch): A lively, informal opportunity to circulate, ask questions, and identify overlap across projects. Posters are strongly encouraged.
• Breakout discussions: Facilitated small-group sessions to identify shared needs (data, tools, compute, evaluation, governance), collaboration opportunities, and concrete next steps—particularly towards future external funding and cross-faculty initiatives.
• Practical takeaways: A curated set of themes, candidate collaborations, and an initial “opportunity map” for AI for Science activity at Lancaster.

We are actively seeking short talks (10–15 minutes) on any activity that fits “AI for Science” in the broadest sense. This includes methodological work, applied case studies, infrastructure/tooling, or evaluation and governance approaches that enable scientific progress.

Examples of suitable topics include (not limited to):

• AI for scientific discovery (new hypotheses, new materials, new mechanisms, new insights)
• AI for simulation and scientific computing (surrogates, emulators, PDE learning, accelerators)
• AI for experiments and measurement (automation, control, adaptive/active learning, lab/field workflows)
• AI for data assimilation and inverse problems (uncertainty quantification, calibration, causal inference)
• AI for earth and environmental science, climate, ecology, biodiversity, geoscience
• AI for health, medicine, life sciences, imaging, genomics, epidemiology
• AI for engineering, energy systems, manufacturing, sensors, robotics
• AI for evaluation and robustness in scientific settings (ground truth scarcity, dataset shift, validation)
• Responsible and trustworthy AI for scientific practice (reproducibility, data governance, ethics)

Poster displays: If you have a poster we will provide space for displays and discussion during the lunch session. We can also cover the cost of printing the poster.

• Academic staff and researchers working in, or curious about, AI-enabled science
• PDRAs and PhD students with AI-for-science methods or applications
• Research software engineers, data specialists, lab/technical teams, and professional services colleagues supporting research
• Anyone interested in building cross-disciplinary collaborations around scientific AI

• 10:00 – 10:15 Welcome and aims for the day (DSAIL)
• 10:15 – 10:45 Framing session: “What counts as AI for Science?” (shared language, examples, evaluation expectations)
• 10:45 – 12:15 Lightning talks (10–15 minutes each) + structured Q&A
• 12:15 – 1:15 Lunch + poster session + networking
• 1:15 – 2:15 Breakout sessions (theme-led groups; capture opportunities and blockers)
• 2:15 – 2:45 Report-back from groups (short summaries, candidate collaborations)
• 2:45 – 3:00 Close: Wrap-up and next steps.

Light refreshments will be available throughout the day. Lunch will also be provided, please indicate dietary requirements via the Eventbrite registration.

• Attend: Register here
• Present: Submit a proposed title + 2–4 sentence summary with your registration
• Poster: Indicate in your registration that you would like to bring a poster (and whether you need DSAIL to pay the printing charge)

Event Venue & Nearby Stays

The Management School, Lancaster University,, Lancaster, United Kingdom

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