School of Management and Technology
Organisational unit: Research School
- Institute for Auditing & Tax
- Institute for production technology and systems
- Institute of Experimental Industrial Psychology
- Institute of Information Systems
- Institute of Knowledge and Information Management
- Institute of Management, Accounting & Finance
- Institute of Management and Organization
- Institute of Marketing
- Institute of New Venture Management
- Institute of Performance Management
Organisation profile
EMPOWERING MINDS. INSPIRING INNOVATIONS. SHAPING TRANSFORMATIONS.
As part of Leuphana University, the School of Management and Technology is a dynamic and innovative community of students and faculty with high-level expertise in the fields of organization studies, responsible management, entrepreneurship, product development process, digital transformation and data science, and psychology and societal transformation. Our core aspiration is driving innovation in management and technology to shape responsible and sustainable transformations. In our research, we pioneer understandings of and solutions to the core challenges of our time, such as digitalization and sustainable production. In our teaching, we challenge conventional wisdom and inspire entrepreneurial thinking and responsible action. In business and society, we team up with local and international partners to contribute to the regional development of northern Germany. We value the interrelationships between disciplines, which is reflected in our interdisciplinary degree programs and collaboration in research.
The School of Management and Technology is home to the disciplines of Accounting and Finance, Business Psychology, Business Information Systems, Engineering, Management and Marketing. We support the respective identities and profile development of the disciplines, while also promoting interdisciplinary research and teaching in the shape of programs of study and research centers. This interdisciplinary approach is characterized by a commitment to responsibility and helping meet societal challenges.
Main research areas
The School of Management and Technology is the academic and professional home to 1,500 bachelor’s, master’s and doctoral students, more than 50 professors, more than 70 research associates and research assistants, 36 professional staff members.
The main themes of the school are reflected in its study programs: The 3 major and 7 minor programs at the College, 5 master's programs and 4 doctoral programs at the Graduate School provide academic training. The doctoral programs focus on (1.) Entrepreneurship, Management and Innovation (EMI), (2.) Information Systems and Data Science, (3.) Engineering and (4.) Management, Finance and Accounting.
In total, we offer 16 programs of study in the disciplines of Business Administration (in particular Accounting and Finance), Business Information Systems, Business Psychology, Engineering and Management.
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Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018, Proceedings - Part III
Brefeld, U. (Editor), Curry , E. (Editor), Daly, E. (Editor), MacNamee, B. (Editor), Marascu, A. (Editor), Pinelli , F. (Editor), Berlingerio, M. (Editor) & Hurley, N. (Editor), 2019, Cham: Springer Verlag. 706 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11054 LNAI)Research output: Books and anthologies › Collected editions and anthologies › Research
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Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2019, Würzburg, Germany, September 16–20, 2019, Proceedings, Part I
Brefeld, U. (Editor), Fromont, E. (Editor), Hotho, A. (Editor), Knobbe, A. (Editor), Maathuis, M. (Editor) & Robardet, C. (Editor), 2020, Cham: Springer Nature Switzerland AG. 766 p. (Lecture notes in computer science; vol. 11906)(Lecture Notes in Artificial Intelligence; vol. 11906)Research output: Books and anthologies › Conference proceedings › Research
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Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2019, Würzburg, Germany, September 16–20, 2019, Proceedings, Part II
Brefeld, U. (Editor), Fromont, E. (Editor), Hotho, A. (Editor), Knobbe, A. (Editor), Maathuis, M. (Editor) & Robardet, C. (Editor), 2020, Cham: Springer Nature Switzerland AG. 732 p. (Lecture notes in computer science; vol. 11906)(Lecture Notes in Artificial Intelligence; vol. 11906)Research output: Books and anthologies › Conference proceedings › Research
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Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2019, Würzburg, Germany, September 16–20, 2019, Proceedings, Part III
Brefeld, U. (Editor), Fromont, E. (Editor), Hotho, A. (Editor), Knobbe, A. (Editor), Maathuis, M. (Editor) & Robardet, C. (Editor), 2020, Cham: Springer Nature Switzerland AG. 804 p. (Lecture notes in computer science; vol. 11906)(Lecture Notes in Artificial Intelligence; vol. 11906)Research output: Books and anthologies › Conference proceedings › Research
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Machine Learning Applications
Arndt, N., Molitor, P. & Usbeck, R., 27.08.2023, In: IT - Information Technology. 65, 4-5, p. 139-141 3 p.Research output: Journal contributions › Other (editorial matter etc.) › Research
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Machine Learning For Determining Planned Order Lead Times In Job Shop Production: A Systematic Review Of Input Factors And Applied Methods
Wolter, F., Rokoss, A. & Schmidt, M., 2025, Conference on Production Systems and Logistics: University of San Ignacio de Loyola Lima, Peru, 18th – 21th March 2025, Proceedings. Herberger, D. & Hübner, M. (eds.). Offenburg: publish-Ing., p. 374-384 11 p. 32. (Proceedings of the ... Conference on Production Systems and Logistics; no. 7).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data
Hoogendoorn, M. & Funk, B., 2018, 1 ed. Cham: Springer International Publishing. 231 p. (Cognitive Systems Monograph; vol. 35)Research output: Books and anthologies › Monographs › Research › peer-review
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Machine learning pipeline for Structure–Property modeling in Mg-alloys using microstructure and texture descriptors
Guru, M. K., Bohlen, J., Aydin, R. C. & Khalifa, N. B., 15.08.2025, In: Acta Materialia. 295, 121132.Research output: Journal contributions › Journal articles › Research › peer-review
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Machine Learning-Supported Planning of Lead Times in Job Shop Manufacturing
Kramer, K., Wagner, C. & Schmidt, M., 2020, Advances in Production Management Systems. The Path to Digital Transformation and Innovation of Production Management Systems - IFIP WG 5.7 International Conference, APMS 2020, Proceedings: The Path to Digital Transformation and Innovation of Production Management Systems IFIP WG 5.7 International Conference, APMS 2020 Novi Sad, Serbia, August 30 – September 3, 2020 Proceedings, Part I. Lalic, B., Marjanovic, U., Majstorovic, V., von Cieminski, G. & Romero, D. (eds.). Cham: Springer Verlag, Vol. 1. p. 363-370 8 p. (IFIP Advances in Information and Communication Technology; vol. 591 IFIP).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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Machine Vision and Navigation
Sergiyenko, O. (Editor), Flores-Fuentes, W. (Editor) & Mercorelli, P. (Editor), 30.09.2019, Cham: Springer International Publishing. 851 p.Research output: Books and anthologies › Book