Univ.-Prof. Dr. habil. Ricardo Büttner, Chaired Professor
- Since 09/2024: Helmut-Schmidt-University/University of the Federal Armed Forces Hamburg, Chaired Professor of Hybrid Intelligence
- 2021–2024: University of Bayreuth, Chaired Professor of Information Systems and Data Science
- 2013–2020: University of Trier, Habilitation (venia legendi, Dr. oec. habil.)
- 2017–2021: HAW Aalen, Professor of Data Science and Director of Machine Learning Center
- 2009–2017: FOM, Professor of Information Systems and Scientific Director of Institute of Management & Information Systems
- 2003–2009: University of Hohenheim, Doctoral thesis (Dr. oec.) in Information Systems within the DFG Priority Research Program 1083
- 2006–2009: BMW AG, Department Head of BMW HR Strategy, Digital Transformation
- 2004–2006: BMW AG, Head of Strategy Team Car IT, Digital Transformation
- 2002–2004: University of Hagen, Business Administration (Dipl.–Kfm.)
- 2002–2004: BMW AG, Product Manager Z4, Z8, X5
- 2000–2002: BMW AG, Product Controller and SAP Project Manager
- 1996–2000: University of Ilmenau, Industrial Engineering (Dipl.-Wirtsch.-Ing.)
- 1994–1999: University of Ilmenau, Computer Science (Dipl.-Inf.)
Author of more than 170 peer-reviewed journal and conference publications (including 51 with A/A* ranking according to VHB, ABDC, CORE); 21 international Best Paper, Best Reviewer, and Service Awards and nominations. Successfully conducted 23 research projects (> 8. million Euro funding from BMBF, BMWK/i, federal states, foundations, and industry).
www.hsu-hh.de/ai | [email protected] | +49 40 6541 2899
Secretariat: Hr. Tamm | [email protected] | +49 40 6541 3942
Luca Eisentraut, M.Sc., Research Associate and Doctoral Student
- Since 01/2025: Helmut-Schmidt-University/University of the Federal Armed Forces Hamburg, Research Associate and Doctoral Candidate at the Chair of Hybrid Intelligence
- 2022–2024: M.Sc. in Mechanical Engineering, University of Bayreuth
- 2020–2023: M.Sc. in Business Administration, University of Bayreuth
- 2017–2020: B.Sc. in Industrial Engineering, University of Bayreuth
My research focuses on developing innovative machine learning methods, particularly in image processing and security applications. With an interdisciplinary background, I am especially interested in the interface between technical and economic research questions. My previous work includes methods for quality control in industrial processes and medical image analysis. At HSU, I primarily conduct research on technologies, opportunities, and risks associated with deepfakes, especially in security-related contexts.
www.hsu-hh.de/ai | [email protected] | +49 40 6541 3943
Pascal Penava, M.Sc., Research Associate and Doctoral Student
- Since 12/2024: Helmut-Schmidt-University/University of the Federal Armed Forces Hamburg, Research Associate and Doctoral Candidate at the Chair of Hybrid Intelligence
- 2023–2024: University of Bayreuth, Research Associate and Doctoral Candidate at the Chair of Information Systems and Data Science
- 2021–2023: M.Sc. in Digitalization and Entrepreneurship, University of Bayreuth
- 2018–2021: B.Sc. in Information Systems, FAU Erlangen-Nürnberg
My research area involves the investigation and development of innovative machine learning approaches with practical relevance. My main interest lies in the field of hybrid intelligence, with a focus on EEG-based human-computer interfaces and the analysis of time series data. Another focus of my research is the application of computer vision methods in various industrial areas.
www.hsu-hh.de/ai | [email protected] | +49 40 6541 3940
Christopher Mai, M.Sc., Research Associate and Doctoral Student
- Since 10/2024: Helmut-Schmidt-University/University of the Federal Armed Forces Hamburg, Research Associate and Doctoral Candidate at the Chair of Hybrid Intelligence
- 2024: University of Bayreuth, Research Associate and Doctoral Candidate at the Chair of Information Systems and Data Science
- 2019–2023: M.Sc. in Mechanical Engineering, BTU Cottbus–Senftenberg
- 2016–2019: B.Sc. in Mechanical Engineering, BTU Cottbus–Senftenberg
My research interests lie in the investigation, development, and optimization of innovative machine learning approaches tailored to practical applications. The primary focus is on the application of computer vision methods in different industrial sectors. This includes, in particular, detecting anomalies in objects during the production process to identify errors at an early stage.
www.hsu-hh.de/ai | [email protected] | +49 40 6541 3937
Leopold Fischer-Brandies, M.Sc., Research Associate and Doctoral Student
- Since 10/2024: Helmut-Schmidt-University/University of the Federal Armed Forces Hamburg, Research Associate and Doctoral Candidate at the Chair of Hybrid Intelligence
- 2021–2024: M.Sc. in Digitalization and Entrepreneurship, University of Bayreuth
- 2017–2021: B.Sc. in Business Administration, University of Bayreuth
My research area encompasses the investigation and development of machine learning methods (particularly in the field of deep learning) and their practical application. Further research interests lie in the development and application of agent-based systems and language models.
www.hsu-hh.de/ai | [email protected] | +49 40 6541 3938
Walter Köhn, M.Sc., Research Associate and Doctoral Student
- Since 10/2025: Helmut-Schmidt-University/University of the Federal Armed Forces Hamburg, Research Associate and Doctoral Candidate at the Chair of Hybrid Intelligence
- 2023–2025: M.Sc. in Finance, Accounting & Taxation, Free University of (with exchange semester at HEC Paris)
- 2020–2023: B.Sc. in Business and Economics, University of Technology Dresden (with exchange semester at Audencia Business School Nantes)
My research primarily focuses on the development and application of modern methods of time series analysis. Based on my background in finance, I focus on applying machine learning methods to identify complex time-dependent patterns in economic and financial data. My other research interests lie in the field of image classification and segmentation for security-relevant systems.
Christian Woesle, M.Systems Eng., ISO Central Secretariat Geneva, External Doctoral Student
- Since 10/2024: Helmut-Schmidt-University/University of the Federal Armed Forces Hamburg, Doctoral Candidate at the Chair of Hybrid Intelligence
- 2022–2024: IT Programme Manager, ISO Central Secretariat, Geneva
- 2020–2022: Founder and Managing Director, startup epanora (Toulouse & La Réunion)
- 2017–2020: Technical Project Manager, Airbus (Munich & Toulouse)
- 2005–2017: Network Architect at a German federal authority in Munich
- 2013–2016: M. Systems Eng., Munich University of Applied Sciences
- 2008–2011: B.Sc. in Information Systems, FOM University Munich
My research focuses on analyzing the current state of AI technology in existing and emerging AI systems, to clearly classify these systems and identify possible degrees of similarity. Based on this, further research is needed to identify and address problem areas, particularly regarding the misuse of AI, bias in AI systems, and safety concerns. My objective is to advance both theoretical knowledge and practical implementation based on real-world use cases.
Norbert Mönks, M.Sc. & MBA, BMW AG, External Doctoral Student
- Since 10/2024: Helmut-Schmidt-University/University of the Federal Armed Forces Hamburg, Doctoral Candidate at the Chair of Hybrid Intelligence
- 2022–2024: MBA in Sustainability Management, SRH Distance University
- Since 2016: IT Specialist & Sub-PDO, BMW AG
- 2014–2017: M.Sc. in IT Management, FOM University Munich
- 2013–2016: Senior IT Consultant, Ventum Consulting GmbH & Co. KG
- 2008–2011: B.Sc. in Information Systems, FOM University Munich
- 2007–2015: Founder and Managing Director, Manathan GmbH
- 2004–2011: IT Manager, IDEO GmbH
My research focuses on analyzing current and future developments in AI technologies, their applications, and their associated challenges. A central aspect of my work is identifying and implementing solutions to existing problems. In particular, I focus on security aspects, such as reducing the potential for misuse and minimizing bias in AI systems, as well as on the impact of AI on sustainability. Alongside theoretical work, I place strong emphasis on the practical implementation of the developed approaches.
Justin Hoffmann, M.A., Officer, External Doctoral Student
- Since 01/2025: Helmut-Schmidt-University/University of the Federal Armed Forces Hamburg, Doctoral Candidate at the Chair of Hybrid Intelligence
- Since 09/2024: M.A. in Management and Media, University of the Bundeswehr Munich
- Since 10/2023: B.A. in Management and Media, University of the Bundeswehr Munich
My research interests lie in advancing the System Dynamics approach through hybrid intelligence. By employing artificial intelligence techniques, particularly large language models, I explore new opportunities for modularization and for improving the accessibility of this approach. The goal of my research is to develop novel practical applications for model-based decision support in order to address the existing and future challenges of an increasingly dynamic and complex environment more efficiently and effectively. In addition, my research focuses on machine learning and deep learning.
Celina Rieck, B.A., Research Assistant
- Since 06/2025: Research Assistant at the Chair of Hybrid Intelligence, Helmut Schmidt University / University of the Federal Armed Forces Hamburg
- Since 01/2025: M.A. studies in Digital Administration and Governance, Helmut Schmidt University / University of the Federal Armed Forces Hamburg
- 2022 – 2024: B.A. studies in Political Science, Helmut Schmidt University / University of the Federal Armed Forces Hamburg
- Since 07/2021: Officer career path, German Federal Armed Forces
My interest is in the integration of learning systems into clinical and psychological contexts, particularly in the areas of prevention and personality research. The central focus lies on the analysis and evaluation of AI-assisted diagnostic and decision-making processes, as well as their ethical, security-related, and societal implications.
Letzte Änderung: 15. October 2025