Research assistant in the research team Digitization and Management

• Artificial Intelligence
  • Machine Learning
  • Deep Learning
• Data Analysis
  • Time Series Analysis/Prediction/Classification
  • Data Augmentation

ANIMATE

• Mater of Science in Media Informatics (MSc), Eberhard Karls University of Tübingen, Tübingen
  • Study abroad semester at the Università degli Studi Roma Tre, Rome (Italy)
  • Internship in the field of data analysis, Daimler AG, Untertürkheim, Germany
  • Master's thesis undertaken at Daimler AG: ‘Classifying Industrial Welding Data Using Support Vector Machines and Neural Networks’
• Bachelor of Science in Media Informatics (BSc), Eberhard Karls Universität Tübingen, Tübingen
• Apprenticeship as an IT specialist in the field of system integration, Deutsche Telekom AG, Regensburg

• D. Kiefer, M. Bauer and F. Grimm: Univariate Time Series Forecasting: Machine Learning Prediction of the Best Suitable Forecast Model based on Time Series Characteristics. In: Proceedings of the 14th International Conference on Human Centred Intelligent Systems (KES-HCIS-21). Rom 2021.
• M. Bauer, D. Kiefer and F. Grimm: Sales Forecasting under Economic Crisis: A Case study of the Impact of the COVID19 Crisis to the predictability of Sales of a Medium-Sized Enterprise. In: Proceedings of the 14th International Conference on Human Centred Intelligent Systems (KES-HCIS-21). Rom 2021.
• F. Grimm, D. Kiefer and M. Bauer: Univariate Time Series Forecasting by Investigating Intermittence and Demand Individually. In: Proceedings of the 14th International Conference on Human Centred Intelligent Systems (KES-HCIS-21). Rom 2021.
• D. Kiefer, C. van Dinther and J. Spitzmüller: Digital Innovation Culture – A Systematic Literature Review. In: Proceeding of the 16. Internationale Tagung der Wirtschaftsinformatik (WI). 16. Auflage. Duisburg-Essen 2021.
• D. Kiefer, F. Grimm, M. Bauer and C. van Dinther, “Demand Forecasting Intermittent and Lumpy Time Series: Comparing Statistical, Machine Learning and Deep Learning Methods,” in Proc. 54rd Hawaii Int. Conf. Syst. Sci., Maui, HI, USA, Jan. 2021.