Institute of Information Systems
Organisational unit: Institute
- Junior professorship for Information Systems, in particular Data Analytics
- Professorship for Computer Engineering
- Professorship for Information Systems, in particular Artificial Intelligence and Explainability
- Professorship for Information Systems, in particular Data Science
- Professorship for Information Systems, in particular Digital Transformation and Information Management
- Professorship for Information Systems, in particular E-Business and Knowledge Management
- Professorship for Information Systems, in particular Machine Learning
- Professorship for Information Systems, in particular Network Science
Organisation profile
At the Institute of Information Systems (IIS) of the Leuphana University we work on innovative topics in Information Systems and Data Science. The main focus is on digital transformation, e-health, e-commerce, business analytics, sports and e-learning. Methodologically, we focus on the development and use of machine learning and artificial intelligence methods for the modeling and solution of data-driven decision problems. Additional quantitative (e.g. graphs, optimization) and qualitative (e.g. interviews, reference modeling) methods complement this spectrum. Cooperating with other universities, companies, and institutions of the civil society plays an important role in our work.
Main research areas
At the Institute of Information Systems there are currently 6 professors and numerous research assistants. Our main research areas include digital transformation, e-health, e-commerce, business analytics, sports, and e-learning. Details can be found on the websites of the work groups and in the central research database of Leuphana. The Institute of Information Systems organized a number of events and conferences at Leuphana (e.g. ITEE 2013, final round of the German National Computer Science Competition 2014, MKWI 2018).
- Published
IT Governance in Scaling Agile Frameworks
Horlach, B., Böhmann, T., Schirmer, I. & Drews, P., 2018, Tagungsband Multikonferenz Wirtschaftsinformatik 2018: Data driven X - Turning Data into Value. Drews, P., Funk, B., Niemeyer, P. & Xie, L. (eds.). Leuphana Universität Lüneburg, Vol. 5. p. 1789-1800 12 p. (MKWI 2018 - Multikonferenz Wirtschaftsinformatik; vol. 2018-March).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
- Published
A health economic outcome evaluation of an internet-based mobile-supported stress management intervention for employees
Ebert, D. D., Kählke, F., Buntrock, C., Berking, M., Smit, F., Heber, E., Baumeister, H., Funk, B., Riper, H. & Lehr, D., 02.2018, In: Scandinavian Journal of Work, Environment and Health. 44, 2, p. 171-182 12 p.Research output: Journal contributions › Journal articles › Research › peer-review
- Published
Propagating Maximum Capacities for Recommendation
Boubekki, A., Brefeld, U., Lucchesi, C. L. & Stille, W., 2017, KI 2017: Advances in Artificial Intelligence: 40th Annual German Conference on AI, Dortmund, Germany, September 25-29, 2017 : proceedings. Cham, Schweiz: Springer, p. 72-84 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10505 LNAI).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
- Published
Deep Learning auf sequenziellen Daten als Grundlage unternehmerischer Entscheidungen: Schwerpunkt Analyse sequenzieller Daten
Funk, B., Dr. Rettenmeier, M. & Lang, T., 10.2017, In: Wirtschaftsinformatik & Management. 9, 5, p. 16-25 10 p.Research output: Journal contributions › Journal articles › Research › peer-review
- Published
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 AG. 231 p. (Cognitive Systems Monograph; vol. 35)Research output: Books and anthologies › Monographs › Research › peer-review
- Published
Predicting Therapy Success For Treatment as Usual and Blended Treatment in the Domain of Depression
van Breda, W. R. J., Bremer, V., Becker, D., Funk, B., Ruwaard, J. & Riper, H., 01.06.2018, In: Internet Interventions. 12, p. 100-104 5 p.Research output: Journal contributions › Journal articles › Research › peer-review
- Published
Bimodal Enterprise Architecture Management: The emergence of a new EAM function for a BizDevOps-based fast IT
Drews, P., Schirmer, I., Horlach, B. & Tekaat, C., 02.11.2017, Proceedings - 2017 IEEE 21st International Enterprise Distributed Object Computing Conference Workshops, EDOCW 2017: 10–13 October 2017 Quebec City, Quebec, Canada, Proceedings. Lapalme, J., Halle, S. & Dijkman, R. (eds.). IEEE - Institute of Electrical and Electronics Engineers Inc., p. 57-64 8 p. (Proceedings - IEEE International Enterprise Distributed Object Computing Workshop, EDOCW; vol. 2017-October).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
- Published
Guest editorial: Special issue on sports analytics
Brefeld, U. & Zimmermann, A., 01.11.2017, In: Data Mining and Knowledge Discovery. 31, 6, p. 1577-1579 3 p.Research output: Journal contributions › Other (editorial matter etc.) › Research
- Published
Frame-based Data Factorizations
Mair, S., Boubekki, A. & Brefeld, U., 25.07.2017, 34th International Conference on Machine Learning, ICML 2017. Precup, D. & Teh, Y. W. (eds.). Red Hook: Curran Associates, p. 2305-2313 9 p. (Proceedings of Machine Learning Research; vol. 70).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
- Published
Distributed robust Gaussian Process regression
Mair, S. & Brefeld, U., 01.05.2018, In: Knowledge and Information Systems. 55, 2, p. 415-435 21 p.Research output: Journal contributions › Journal articles › Research › peer-review