معرفی
Roles & Affiliations: Daniel Einsiedel is a Research Associate and Doctoral Student at the Department of Food Informatics/Computational Science Hub (CSH), University of Hohenheim. He is funded by a Dutch machine manufacturer to investigate data-driven analysis of manufacturing processes, focusing on quality fluctuations and causes using image recognition, time series, and correlation analysis.
- Secretariat: Team within the Institute of Food Science and Biotechnology
- Consultation hours: By appointment
Education:
- M.Sc. Food Science and Engineering (2019–2022), University of Hohenheim
- Research Stay (2018–2019), University of Knoxville, Tennessee, USA
- B.Sc. Food Science and Biotechnology (2015–2019), University of Hohenheim
Research Interests: Daniel’s work bridges computer science and food engineering, emphasizing interdisciplinary solutions for manufacturing processes. His methodologies include machine learning, image-based quality analysis, and predictive modeling for industry optimization.
Labs/Teams: Active contributor to the Computational Science Hub (CSH), collaborating with industry partners to apply AI and Industry 4.0 technologies in food processing.
