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).
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Probabilistic movement models and zones of control
Brefeld, U., Lasek, J. & Mair, S., 15.01.2019, In: Machine Learning. 108, 1, p. 127-147 21 p.Research output: Journal contributions › Journal articles › Research › peer-review
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Principled Interpolation in Normalizing Flows
Fadel, S., Mair, S., da Silva Torres, R. & Brefeld, U., 09.2021, Machine Learning and Knowledge Discovery in Databases. Research Track: European Conference, ECML PKDD 2021, Bilbao, Spain, September 13–17, 2021, Proceedings, Part II. Oliver, N., Pérez-Cruz, F., Kramer, S., Read, J. & Lozano, J. A. (eds.). Cham: Springer Nature AG, p. 116-131 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12976 LNAI).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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Preventive Emergency Detection Based on the Probabilistic Evaluation of Distributed, Embedded Sensor Networks
Busch, B.-H., Kujath, A., Witthöft, H. & Welge, R., 2011, Ambient Assisted Living: 4. AAL-Kongress 2011 in Berlin. Wichert, R. & Eberhardt, B. (eds.). Springer, p. 159-179 21 p. (Advanced Technologies and Societal Change).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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Preventive Diagnostics for cardiovascular diseases based on probabilistic methods and description logic
Busch, 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
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Preliminary data on help‐seeking intentions and behaviors of individuals completing a widely available online screen for eating disorders in the United States
Fitzsimmons-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
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Predictive modeling in e-mental health: A common language framework
Becker, 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
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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
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Predicting Therapy Success and Costs for Personalized Treatment Recommendations Using Baseline Characteristics: Data-Driven Analysis
Bremer, 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
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Predicting the Individual Mood Level based on Diary Data
Bremer, 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
- Published
Predicting the future performance of soccer players
Arndt, 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