Transforming nutrition with artificial intelligence
An Erasmus+ Blended Intensive Programme
28 September – 2 October 2026 · Lemnos, Greece
University of the Aegean, Department of Food Science and Nutrition
About the Programme
Dietary assessment is one of the most challenging problems in nutrition science. Self-reported intake is prone to bias, traditional tools are time-consuming, and translating raw dietary data into actionable insights remains difficult at scale. Artificial intelligence is changing this – but most nutrition professionals have had little opportunity to engage with these tools in a structured, critical way.
This Erasmus+ Blended Intensive Programme brings together students and early-career researchers from across Europe to explore how AI methods are transforming the way we measure, interpret, and act on dietary data. Over five intensive days on the island of Lemnos, participants will work with real-world tools (including large language models, image-based food recognition systems, and predictive modelling approaches) guided by experts from the University of the Aegean and KU Leuven.
The programme is built around three interconnected themes: AI-enabled dietary assessment, personalised nutrition, and data-driven behaviour change strategies. It combines lectures, hands-on practical sessions, and a collaborative international group project, and is specifically designed for participants with no prior programming or data analysis experience.
Programme Structure
The programme follows a blended format with three phases:
A. Before the mobility: Participants complete a short online module covering introductory materials and a pre-reading assignment, so that everyone arrives with a shared foundation regardless of their background.
B. In-person mobility (28 Sep – 2 Oct 2026): Five intensive days in Lemnos combining lectures, practical sessions, and group project work:
- Day 1 – Foundations: Overview of dietary assessment methods, measurement error and bias, and an introduction to AI concepts for non-specialists.
- Day 2 – AI Tools: Image-based dietary assessment, NLP and LLM approaches, sensor and wearable data, and formation of international project groups.
- Day 3 – Hands-on Applications: Practical sessions on LLM-based assessment, image analysis workflows, multi-source data integration, and an introduction to machine learning for dietary data.
- Day 4 – From Data to Decisions: Diet quality indices, personalised nutrition, behaviour change strategies, and ethics, bias and GDPR in dietary AI.
- Day 5 – Integration and Future Directions: Future trends in multimodal AI, final group project presentations, and closing discussion.
C. After the mobility: Participants complete a post-evaluation quiz to consolidate learning and provide feedback on the programme.
Learning Outcomes
By the end of this programme, participants will be able to:
- Describe the main methods of dietary assessment and their limitations in relation to measurement error and misreporting
- Explain how AI approaches (including image recognition, natural language processing, and predictive modelling) can address key challenges in dietary assessment
- Use AI-based tools and workflows to process and interpret dietary data in practical, hands-on settings
- Critically evaluate the validity, feasibility, and scalability of AI-based dietary assessment methods
- Apply ethical reasoning to questions of data quality, algorithmic bias, transparency, and GDPR compliance in nutrition AI
- Collaborate in international interdisciplinary teams to design and present an AI-assisted nutrition solution
Who Should Apply
This programme is open to students and early-career researchers from universities participating in the Erasmus+ programme, working in nutrition, dietetics, food science, public health, or related health disciplines. Both undergraduate students in their final year and postgraduate students are welcome to apply.
No prior experience in programming, statistics, or data analysis is required. The programme is intentionally designed for participants from non-technical backgrounds, with an emphasis on conceptual understanding, practical tool use, and critical thinking rather than coding.
The working language of the programme is English.
Practical Information
Dates: 28 September – 2 October 2026
Location: Lemnos, Greece – University of the Aegean
Credits: 3 ECTS
Available places: 20
Working language: English
Programming experience required: None
Application deadline: TBA
Erasmus+ Funding Eligible participants from partner universities may apply for an Erasmus+ mobility grant to support travel and subsistence costs. The grant covers a contribution towards accommodation costs during the mobility period. Students should contact their home institution’s Erasmus+ office to confirm eligibility and apply through their university’s standard mobility procedures.
Location
The in-person component of the programme takes place on the island of Lemnos, in the northern Aegean Sea. Lemnos is home to one of the University of the Aegean’s campuses, combining a productive academic environment with the calm and character of an Aegean island.
The island is served by direct flights from Athens (approximately 1 hour) and Thessaloniki. Detailed travel information, including accommodation recommendations, will be shared with accepted participants upon confirmation of their place.
The Team
Vasiliki (Sila) Bountziouka, MSc, PhD, AFHEA Assistant Professor in Biostatistics, Department of Food Science and Nutrition, University of the Aegean. Sila’s research focuses on nutritional epidemiology, dietary assessment methodology, and the application of statistical and computational methods in nutrition research.
Stathis Kaloudis, PhD Assistant Professor in Computer Simulations and Informatics, Department of Food Science and Nutrition, University of the Aegean. Stathis works at the intersection of computational methods, data analysis, and food and nutrition science.
FAQ
Do I need to know how to code or use data analysis software? No. The programme is designed for participants with no programming experience. All hands-on sessions use accessible tools with guided instruction.
What equipment do I need to bring? A laptop with an internet connection is sufficient. All software tools used during the programme are browser-based and free of charge. Specific setup instructions will be shared before the mobility.
Is financial support available? Yes. Eligible participants from partner universities may receive an Erasmus+ mobility grant covering travel costs and a contribution towards accommodation. Please contact your home institution’s Erasmus+ coordinator for details on how to apply.
How will I be assessed? Assessment is based on active participation throughout the five days and the final group project presentation on Day 5. Successful completion leads to the award of 3 ECTS credits.
What is the application process? [ application process here – form, required documents, selection criteria.]
How many places are available? The programme is limited to 20 participants to ensure an interactive and high-quality learning experience.
Will I receive a certificate? Yes. All participants who successfully complete the programme will receive a certificate of attendance issued by the University of the Aegean, alongside the 3 ECTS credit award.
Apply / Contact
Applications are open. [Link to application form]
For questions about the programme content, contact: vboun@aegean.gr · stathiskaloudis@aegean.gr
For questions about Erasmus+ funding and eligibility, please contact your home institution’s Erasmus+ office.
Computer Simulation, Genomics and Data Analysis Laboratory Department of Food Science and Nutrition, University of the Aegean