By appointment

Programme Director of the MSc Operations Management Programme

• Mathematics, Statistics, Operations Research
• Computer Science
• Data Science, Machine Learning

• Data Science, Machine Learning
• Scientific Computing
• Quantitative Rism Management (Market Risk and Credit Risk)

• Graduate in Mathematics (Heidelberg University)
• Doctorate in Mathematics at the Interdisciplinary Centre of Scientific Computing, Heidelberg University
• 2004 to 2011 Business Consultant at Ernst &Young in the sector of Financial Services Risk Management and Derivatives Valuation Center
• Since 2011 Professor of Quantitative Methods at ESB Business School, Reutlingen University

Articles in editor's volumes:

Anja Braun, Peter Kleine-Möllhoff, Volker Reichenberger, Stephan Seiter: Tools, Methods and Standards for the Assessment of Material Efficiency Aspects in Small and Medium Sized Enterprises (SMEs), Journal of Engineering, Management and Operations 2018, p. 1 - 28, LIT, Münster, ISBN 978-3-643-99768-5 

Anja T. Braun, Peter Kleine-Moellhoff, Volker Reichenberger, Stephan Seiter: Survey concerning enablers for material efficiency activities in manufacturing, their supply chains and the transformation towards circular economy, Reutlinger Diskussionsbeiträge zu Marketing & Management, Uni Tübingen, 2018-04-21, http://hdl.handle.net/10900/81786, ISBN 1863-0316

Peer-reviewed:

Braun, Anja; Kleine-Möllhoff, Peter; Reichenberger, Volker; Seiter, Stephan (2018): Case Study Analysing Potentials to Improve Material Efficiency in Manufacturing Supply Chains, Considering Circular Economy Aspects. In: Sustainability 10 (3), 1- 12. DOI: 10.3390/su10030880

Kleine-Moellhoff, Peter; Braun, Anja T.; Reichenberger, Volker; Seiter, Stephan (2018): Approach to Enable a Material Efficiency-Strategy for Small and Medium Sized Manufacturing Enterprises. In: Procedia CIRP 69, S. 787–792. DOI: 10.1016/j.procir.2017.11.106

Articles in journals:

Anja T. Braun, Peter Kleine-Moellhoff, Volker Reichenberger and Stephan Seiter Case Study Analysing Potentials to Improve Material Efficiency in Manufacturing Supply Chains, Considering Circular Economy Aspects. Sustainability 2018, 10(3), 880; MDPI, Basel, DOI:10.3390/su10030880

Reichenberger, Volker; Schieborn, Dirk (2018): Maschinelle Lernverfahren als Benchmarking für klassische Ratingverfahren. In: Zeitschrift für das gesamte Kreditwesen (24-2018), S. 20– 23. Online verfügbar unter www.kreditwesen.de/kreditwesen/themenschwerpunkte/aufsaetze/maschinellelernverfahren-benchmarking-fuer-klassische-ratin-id53108.html

Academic Publications

Reichenberger V. On the selection of machine learning Models. In: Bauer W, Sihn W, Ohlhausen P, editors. Journal of Engineering, Management and Operations, Band 1. Zürich: Lit Verlag; 2019. p. 55–64. ISBN: ISBN 978-3-643-99768-5.

Braun, Anja; Kleine-Möllhoff, Peter; Reichenberger, Volker; Seiter, Stephan (2018): Survey concerning enablers for material efficiency activities in manufacturing, their supply chains and the transformation towards circular economy. Hg. v. Carsten Rennhak (Universität der Bundeswehr München) und Gerd Nufer (Hochschule Reutlingen) (Reutlinger Diskussionsbeiträge zu Marketing & Management). DOI: 10.15496/PUBLIKATION-23180. Seiten: 49