By arrangement

Research assistant in the research team Digitization and Management

• Artificial Intelligence
• Machine learning
• Deep Learning
• Digitization & Management
• Industry 4.0

• ANIMATE

Professional Experience

• Science & Research, ESB Business School
• Management Consulting, Barkawi Management Consultants
• Management Consulting, goetzpartners
• Private Equity, CAPCELLENCE
• Lean Management Consulting, STAUFEN.SHANGHAI
• Management Consulting, TARGUS Management Consulting
• SYNCHRO Inhouse Consulting, TRUMPF North America
• Inhouse Consulting, Carl Zeiss Vision

Academic Education

• PhD Candidate, Artificial Intelligence, Karlsruhe Institute of Technology (KIT)
• Operations Management (M. Sc.), ESB Business School
• Business & Entrepreneurship, Cambridge Judge Business School
• Computer Science & Business Administration ,University Bologna
• Maschinenbau – Wirtschaft und Management (B. Eng.), Aalen University

Scholarships

• 100 KI Talente Stipendiat, Fraunhofer IAO
• Studienstiftung des deutschen Volkes
• Elevate VDI – Verein Deutscher Ingenieure
• DAAD - Deutscher Akademischer Austauschdienst
• McKinsey Firsthand Program
• BCG Emerald Talent Program

• G. Blessing and D. Kiefer: Digital Skills of Procurement Employees and their Attitudes toward Digital Technologies. In: Proceedings of the 14th International Conference on Human Centred Intelligent Systems (KES-HCIS-21). Rom 2021.
• 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.
• Bauer M., Dinther C. van, & Kiefer D., “Machine Learning in SME: An Empirical Study on Enablers and Success Factors: An Empirical Study on Enablers and Success Factors,” AMCIS 2020 Proceedings 3, no. 3, 2020.
• Kiefer, D., Ulmer, A. & Dinther, C. van. (2019). Application of Artificial Intelligence to optimize forecasting capability in procurement. In U. Kloos, N. Martinez, & G. Tullius (Hrsg.), Wissenschaftliche Vertiefungskonferenz. Tagungsband 2019 (1. Aufl., S. 69–80). Reutlingen: Reutlingen University. doi: https://doi.org/10.5281/zenodo.3539397
• Eberl, A., Fallert, B., Kiefer, D., Leuschner, D., Mastroianni, L., Richter, P., . . . Palm, D. (2018). Methoden zur Sofortpreis-kalkulation von CNC-Drehteilen. ZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb, 113(12), 835–839. doi.org/10.3139/104.112020