Track / Overview

The United Nations states "End hunger, achieve food security and improved nutrition and promote sustainable agriculture" as one of its sustainable development goals by the target date of 2030. To achieve these goals, global food and agriculture systems will require profound changes, in which big data and AI technologies can play significant roles.

In the past decade, a considerable amount of work has been done in biomedical predictive modelling. While there are extensive resources available for the biomedical domain, the food and nutrition ones are relatively low AI-resourced. In the last five years, several studies have been focused on relevant food information extraction from textual data, food image recognition, food portion estimation, food ontology alignment, etc.
Despite some recent studies, nutrition and food safety do not use the full potential of AI and Machine learning. Developing AI resources to merge heterogeneous data sets (ex: linking food and nutrition data with biomedical and environmental data) can provide a useful recommendation to satisfy the need for safe, environmentally sustainable and healthy food.

The focus on this track is to provide an overview of AI methods that have already existed for food and nutrition data, together with methods for linking biomedical research data with food and nutrition data as well as on methods that address key challenges arising in application areas relevant to personalized nutrition and medicine, and food safety and traceability.

Track / Schedule

The Future of Personalised Nutrition; Big data, Remote Trials and Multi-omics from the ZOE PREDICT Programme

With Sarah Berry

Predicting Customer Churn for Beverage Machines

With Mirko Salomon


Foodome Project: Tackling the Complexity of Food Systems

With Giulia Menichetti

Digital Twins as Enabler for Data-driven Improvements in the Industrial Manufacturing of Food and Feed

With Ali Baajour


Food Image Recognition Context

With Gaurav Singhal


Track / Speakers

Ali Baajour

Data Scientist, Bühler AG

Giulia Menichetti

Senior Research Scientist, Barabasi Lab

Mirko Salomon

Advanced Analytics Specialist, Nestlé

Sarah Berry

King's College, London

Gaurav Singhal

Data Scientist, Oviva

Track / Co-organizers

Fabio Mainardi

Senior Data Scientist, Nestle

Tome Eftimov

Jožef Stefan Institute

Barbara Koroušić Seljak

Associate Professor, Jozef Stefan Institute

AMLD EPFL 2022 / Tracks & talks

AMLD Keynote Session – Monday morning

Marcel Salathé, Lenka Zdeborová, Carmela Troncoso, Chiara Enderle, Patrick Barbey, Thomas Wolf, Gunther Jansen, Laure Willemin, Simon Hefti, Arthur Gassner

10:00-12:00 March 28Auditorium A

AI & Physics

Francesca Mignacco, Gert-Jan Both, Michael Unser, Thomas Asikis, Dalila Salamani, Pietro Rotondo, Tom Beucler, Giulio Biroli

12:30-18:00 March 285BC

AI & Pharma

Asif Jan, Jonas Richiardi, Patrick Schwab, Naghmeh Ghazaleh, Alexander Büsser, Carlos Ciller, Caibin Sheng, Silvia Zaoli, Félix Balazard, Giulia Capestro, Marianna Rapsomaniki, Martijn van Attekum

13:30-17:30 March 281BC

AMLD / Global partners