1st Workshop on Computational Gastronomy (CoGamy): Data Science for Food and Cooking

12th November 2025. 8:30-12:30 Hybrid Workshop at ICDM 2025.

Workshop Overview

Gastronomy, the art of selecting, preparing, serving, and enjoying fine food, has long been regarded as an artistic discipline, despite numerous efforts to establish its scientific foundations. However, the recent availability of high-quality datasets is fostering the investigation of gastronomy from a data science perspective. This is the vision portrayed by computational gastronomy, a data science that blends food, data, and the power of computation for achieving data-driven food innovations.

Computational gastronomy emerges as an interdisciplinary field that blends food, data, and computational techniques to foster data-driven innovations in food science and culinary arts and investigating questions such as: Why do we eat what we eat? What is the molecular basis of the ﬂavor, of ingredients or recipes? Can we quantify the taste of a recipe? How do we measure the nutritional proﬁle of a recipe? How does one make sense of contradictory assertions about the health consequences of food ingredients? How have world cuisines evolved? Can we design a tasty and healthy recipe?

This workshop aims to explore the application of data mining, machine learning, and artificial intelligence techniques in gastronomy. As the culinary landscape continues to evolve with digital transformation, this workshop provides a platform for researchers, data scientists, and industry professionals to investigate methodologies for extracting valuable insights from diverse food-related datasets.

Topics of Interest

We invite submissions covering a broad spectrum of topics related to computational gastronomy, including but not limited to:

Data-driven analysis of food preferences and dietary habits
Molecular basis of flavor perception and ingredient interactions
Quantification of taste and sensory experiences using computational techniques
Nutritional profiling of recipes and health impact analysis
Resolving contradictory assertions on food ingredients and health outcomes
Evolution of world cuisines from a data science perspective
Generative AI for new recipe creation
Personalized dietary recommendations based on machine learning models
Food-chemical graphs and graph neural networks for food pairing
Food identification via spectral analysis and image recognition
Categorization and clustering of food ingredients and recipes
Predictive models for nutrition and health impacts
Large Language Models (LLMs) for food science applications
Food security, safety, and fraud detection using AI and data mining
Real-world experiments in food pairing and computational gastronomy

Interdisciplinary Focus

CoGamy is highly interdisciplinary, bringing together experts from diverse fields such as food science, gastronomy, biology, chemistry, computer science, and data science. It provides a unique opportunity to exchange ideas, identify research challenges, and discuss cutting-edge developments in applying data science, machine learning, and artificial intelligence to food analytics.

Submission Guidelines

We welcome submissions of research papers, case studies, and experimental findings. The contributions should present novel methodologies, frameworks, and experimental results in computational gastronomy. Due to the nature of the topic, we encourage submissions that include real-world experiments with food (e.g., food pairing studies).

Accepted papers will be included in the ICDM Workshop Proceedings (separate from ICDM Main Conference Proceedings), and each workshop paper requires a full registration.

Papers must be formatted and written according to the Submission Guidelines on the ICDM 2025 conference web site.

Submit a paper

Important Dates

Workshop papers submission: Aug 29, 2025 Sep 7, 2025
Notification of workshop papers acceptance to authors: Sep 15, 2025 Sep 19, 2025
Early Bird Registration deadline: September 24, 2025 Sep 30 2025
Workshop date: Nov 12, 2025 in the morning

Organizers and Contact Information

Prof. Ganesh Bagler, IIIT-Delhi, bagler@iiitd.ac.in
Prof. Donghyeon Park, Sejong University, parkdh@sejong.ac.kr
Prof. Andrea Vitaletti (main contact), Sapienza University of Rome, vitaletti@diag.uniroma1.it