We focus on learning combined modalities (cooking recipes and food images), analyzing differences in how a machine would objectively label an image compared to how a human subjectively does, and estimating the population health level from social media images.

The major goal of the project is to understand the food habits from social media images. This includes: training machine learning models for image auto-tagging and content extraction from noisy hashtags; predicting population level health statistics; monitoring temporal and regional trends in food consumption and its implications; learning models that can achieve in depth analysis of food images through the use of large scale cooking recipe data collected from the web.

Research Areas


Ingmar Weber

Amaia Salvador

Enes Kocabey

Mustafa Camurcu

Yusuf Aytar

Ferda Ofli

Raggi al Hammouri