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).
- 2018
- 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
Multi-Agent Path Finding with Kinematic Constraints for Robotic Mobile Fulfillment Systems
Merschformann, M., Xie, L. & Erdman, D., 2018, arXiv, 38 p. (ArXiv.org).Research output: Working paper › Working papers
- Published
Supporting Diffusion of IoT Solutions Exemplified by the ChainPORT Initiative
Tesse, J., Schirmer, I., Drews, P., Saxe, S. & Baldauf, U., 2018, Proceedings of the 24th Americas Conference on Information Systems AMCIS 2018: Digital Disruption, AMCIS 2018. Association for Information Systems, 10 p. (Proceedings of the Americas Conference on Information Systems (AMCIS); vol. 2018).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
- Published
The impact of partially missing communities on the reliability of centrality measures
Martin, C., 2018, Complex Networks & Their Applications VI: Proceedings of Complex Networks 2017 (The 6th International Conference on Complex Networks and Their Applications). Springer, Vol. 1. p. 41-52 12 p. (Studies in Computational Intelligence; vol. 689).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
- 2017
- Published
A Unified Contextual Bandit Framework for Long- and Short-Term Recommendations
Tavakol, M. & Brefeld, U., 30.12.2017, Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2017 Skopje, Macedonia, September 18 – 22, 2017; Proceedings, Part II. Ceci, M., Hollmen, J., Todorovski, L., Vens, C. & Dzeroski, S. (eds.). Springer, Vol. 2. p. 269-284 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10535 LNAI).Research output: Contributions to collected editions/works › Article in conference proceedings › 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
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
Metaheuristics approach for solving personalized crew rostering problem in public bus transit
Xie, L., Merschformann, M., Kliewer, N. & Suhl, L., 10.2017, In: Journal of Heuristics. 23, 5, p. 321-347 27 p.Research output: Journal contributions › Journal articles › Research › peer-review
- Published
What’s Hot: Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data
Hoogendoorn, M. & Funk, B., 28.09.2017Research output: other publications › Articles in scientific forums or blogs › Research › peer-review