Theses

Final/project theses at our department shall transfer methods from the areas of the Internet of Things (IoT), machine learning, artificial intelligence, and adaptive software systems to the food value chain with a focus on food processing. Each thesis is to be conducted with students on an equal footing in a collaborative supervisory approach. The goal of each thesis is to achieve high quality through the supervision of a member of the department, resulting in a scientific publication.

The depth required, as well as the scope of analysis and evaluation, will be determined in consultation with the supervisor depending on the thesis objective (bachelor's, master's, or project thesis). In particular, for most topics the amount of programming activity can be varied in consultation with the students; up to conceptual work or literature analysis without programming. The papers can be written either in German or English.


Open Bachelor's/Master's Theses and Project Works

Each thesis can be written in German or English. However, in some cases the full topic description is only available in German. For any question regarding the topics, please do not hesitate to contact the responsible person.

Food Pairing and Artificial Intelligence

Kontakt: Leonie Boller (E-Mail), Personal page & Dana Jox (E-Mail), Personal page

MA/PW

Using machine learning for anomaly detection in a specific food process

Contact: Dana Jox (E-Mail), Personal page

BA/MA/MP

Development of a Publication Miner for LLM oriented Knowledge Extraction in Nutrition and Health Research

Kontakt: Falk Gogolla (E-Mail), Personal page

BA/MA/MP

Comparison of Approaches for the Simulation of Food Processing System

Contact: Christian Krupitzer (E-Mail), Personal page

BA/MA

Internet of Things, Big Data, and Artificial Intelligence in the Food Industry

Contact: Christian Krupitzer (E-Mail), Personal page

BA/MA/MP

Population balance modeling of a spray agglomeration process (with Prof. Kohlus)

Contact: Christian Krupitzer (E-Mail), Personal page

MA/MP

Implementing a machine learning approach to analyze emerging risks in food safety

Contact: Christian Krupitzer (E-Mail), Personal page

BA/MA/MP

Conceptualization and Modelling of a Digital Food Twin

Contact: Christian Krupitzer (E-Mail), Personal page

BA/MA/MP

Digitalization potential for sustainability certification in diff. food product categories

Contact: Christian Krupitzer (E-Mail), Personal page

 
BA/MA/MP

Optimization of a Python pipeline for the analysis of data from time series

Contact: Daniel Einsiedel (E-Mail), Personal Page

BA/MA

Intelligent System to Monitor Food in the Food Supply Chain

Contact: Elia Henrichs (E-Mail), Personal page

BA/ MA/ MP

BA = Bachelor thesis; MA = Master thesis; MP = Projektwork for Master; HR = Humboldt Reloaded

Procedure

Please contact the person listed in the topic description. Please attach a current curriculum vitae and a transcript of academic achievements. You can discuss the topic in detail in a subsequent meeting.

Please avoid contacting multiple research assistants at the same time without informing them. If several topics with different supervisors are relevant to you, either contact all relevant people at the same time in one email (using the CC function) or write to the contact person listed below. This will help to reduce the effort.

Cooperation with companies: In principle, we are also open to supervise theses with companies or other research institutions. If you have worked out an exciting and scientifically relevant research question with a cooperation partner, please do not hesitate to contact us. 

Your own topic suggestions: Of course, we are always open to suggestions for topics from students. To do so, please familiarize yourself with the research topics in the department and send them a short synopsis (about 1 page) with the topic.

If you are interested in a Master's thesis with a company, have your own topic suggestions or general questions, please contact Christian Krupitzer.

Guide

Here you will find the guidelines for writing theses.

Templates

We recommend using the LaTeX-Template of the subject. LaTeX is a text description language that separates content from presentation. The language has its strength especially for scientific works.