Food Informatics (150L)

The Department of Food Informatics operates interdisciplinary at the interface of food science, biotechnology, and computer science. The research focuses on the digitalization of food production in a holistic approach that also includes the food supply chain, traders/distributors, and consumers. In cooperation with partners from industry and research, we transfer and optimize approaches, methods, and technology from the fields of artificial intelligence, predictive data analysis, Industry 4.0, adaptive software systems, and the Internet of Things to the domain of food processing.

Our Department is associated to the Computational Science Hub of the University of Hohenheim and it is part of the Institute of Food Science and Biotechnology.

Contact

Department of Food Informatics (150L)
Fruwirthstr. 21
Building 01.39 | Room 122
70599 Stuttgart

0711 459 23664
E-Mail


News

The Department of Food Informatics at the 6th IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS 2025) [18.09.2025]

Pia Schweizer, Daniel Einsiedel, and Elia Henrichs from the Department of Food Informatics present their conference papers at the 6th IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS 2025, peer-reviewed) in Tokyo, Japan.more


Florian Kaltenecker receives two Awards for his outstanding Master’s Thesis [12.08.2025]

As part of the Dies academicus at the University of Hohenheim on July 4, 2025, Florian Kaltenecker was honored with two awards for his outstanding master’s thesis: the Professor Wild Award and the Johannsen Bioeconomy Award.more


New Publication in MDPI Chemosensors [21.07.2025]

Julia Senge from the Department of Food Informatics is author of the publication "Integrating Sensor Data, Laboratory Analysis, and Computer Vision in Machine Learning-Driven E-Nose Systems for Predicting Tomato Shelf Life" in MDPI Chemosensors (Impact Factor: 3.7).more


Master thesis in AI with Max-Rubner-Institut [25.06.2025]

In cooperation with the Max Rubner Institute we offer a master thesis on the topic: Use of a Large Language Model for automated answering of a quality assessment questionnaire for nutrient data from the scientific literature more


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