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).
- PublishedPreventive Diagnostics for cardiovascular diseases based on probabilistic methods and description logicBusch, B.-H., Welge, R., Weiss, C. & Bette, M., 2010, Proceedings of the 2010 IADIS European Conference on Data Mining 2010 at the IADIS Multi Conference on Computer Science and Information Systems 2010. IADIS Press, p. 95-100 6 p. (Proc. of the IADIS Int. Conf. Intelligent Systems and Agents 2010, Proc. of the IADIS European Conference on Data Mining 2010, Part of the MCCSIS 2010).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review 
- PublishedPreliminary data on help‐seeking intentions and behaviors of individuals completing a widely available online screen for eating disorders in the United StatesFitzsimmons-Craft, E. E., Balantekin, K. N., Graham, A. K., DePietro, B., Laing , O., Firebaugh, M.-L., Smolar, L., Park, D., Mysko, C., Funk, B., Taylor, C. B. & Wilfley, D. E., 01.09.2020, In: The International journal of eating disorders. 53, 9, p. 1556-1562 7 p.Research output: Journal contributions › Journal articles › Research › peer-review 
- PublishedPredictive modeling in e-mental health: A common language frameworkBecker, D., van Breda, W., Funk, B., Hoogendoorn, M., Ruwaard, J. & Riper, H., 01.06.2018, In: Internet Interventions. 12, Juni 2018, p. 57-67 11 p.Research output: Journal contributions › Scientific review articles › Research 
- PublishedPredicting Therapy Success For Treatment as Usual and Blended Treatment in the Domain of Depressionvan 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 
- PublishedPredicting Therapy Success and Costs for Personalized Treatment Recommendations Using Baseline Characteristics: Data-Driven AnalysisBremer, V., Becker, D., Kolovos, S., Funk, B., van Breda, W., Hoogendoorn, M. & Riper, H., 21.08.2018, In: Journal of Medical Internet Research. 20, 8, 11 p., e10275.Research output: Journal contributions › Journal articles › Research › peer-review 
- PublishedPredicting the Individual Mood Level based on Diary DataBremer, V., Becker, D., Funk, B. & Lehr, D., 06.2017, Proceedings of the 25th European Conference on Information Systems, ECIS 2017. AIS eLibrary, p. 1161-1177 17 p. (Proceedings of the 25th European Conference on Information Systems, ECIS 2017).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review 
- PublishedPredicting the future performance of soccer playersArndt, C. & Brefeld, U., 01.10.2016, In: Statistical Analysis and Data Mining. 9, 5, p. 373-382 10 p.Research output: Journal contributions › Journal articles › Research › peer-review 
- PublishedPredicting the Difficulty of Exercise Items for Dynamic Difficulty Adaptation in Adaptive Language TutoringPandarova, I., Schmidt, T., Hartig, J., Boubekki, A., Jones, R. D. & Brefeld, U., 15.08.2019, In: International Journal of Artificial Intelligence in Education. 29, 3, p. 342-367 26 p.Research output: Journal contributions › Journal articles › Research › peer-review 
- PublishedPredicting recurrent chat contact in a psychological intervention for the youth using natural language processingHornstein, S., Scharfenberger, J., Lueken, U., Wundrack, R. & Hilbert, K., 12.2024, In: npj Digital Medicine. 7, 1, 9 p., 132.Research output: Journal contributions › Journal articles › Research › peer-review 
- PublishedPredicting online user behavior based on Real-Time Advertising DataStange, M. & Funk, B., 06.2016, Proceedings of the Twenty-Fourth Conference on Information Systems (ECIS) 2016. AIS eLibrary, 14 p. (Research Papers; no. 152).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review 
