Projects per year
Organisation profile
Organisation profile
The Business Informatics working group, in particular Data Science, headed by Prof Dr Burkhardt Funk, is dedicated to the development and application of data-driven methods for decision support in companies and public institutions.
Main research areas
The research focus lies on the use of data science and machine learning to analyse large amounts of data in order to optimise processes and decisions. A central topic is the development of intelligent systems that support decisions through data-based predictions. Fields of application include healthcare and various operational functions (e.g. marketing, accounting). We have developed approaches for predicting the effectiveness and personalisation of healthcare interventions, methods for extracting knowledge from documents (business documents, scientific papers) and for optimal budget allocation in marketing.
Keywords
- Business informatics
Fingerprint
Research collaborations from the last five years
Profiles
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Fatemeh Ghoochani
- Professorship of Information Systems, in particular Data Science - Research associate
Person: Academic staff
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Laurin Luttmann
- Professorship of Information Systems, in particular Data Science - Research associate
Person: Academic staff
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LStartupLab: Leuphana Startup Lab für Innovation, Transformation & Gründung
Funk, B. (Project manager, academic), Usbeck, R. (Co-Projectmanager, academic), Seibel, A. (Co-Projectmanager, academic), Mah, D.-K. (Co-Projectmanager, academic), Wille, C. (Coordination) & Japsen, A. (Coordination)
01.08.25 → 31.07.28
Project: Research
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ExRePo: KI-basierte Extraktion von Rechnungspositionen
Funk, B. (Project manager, academic)
01.07.24 → 30.09.26
Project: Research
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Knowledge management in software companies
Funk, B. (Project manager, academic), Niemeyer, P. (Project manager, academic) & Bachmann, A. (Project staff)
01.06.11 → …
Project: Transfer (R&D project)
Research output
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Learning to Solve the Min-Max Mixed-Shelves Picker-Routing Problem via Hierarchical and Parallel Decoding
Luttmann, L. & Xie, L., 02.01.2026, Learning and Intelligent Optimization: 19th International Conference, LION 19, Prague, Czech Republic, June 15–19, 2025, Proceedings, Part I. Zhang, Y., Hladik, M. & Moosaei, H. (eds.). Springer International Publishing, Vol. 1. p. 32-51 20 p. (Lecture Notes in Computer Science; vol. 15744 LNCS).Research output: Contributions to collected editions/works › Chapter › peer-review
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Capitalizing on natural language processing (NLP) to automate the evaluation of coach implementation fidelity in guided digital cognitive-behavioral therapy (GdCBT)
Zainal, N. H., Eckhardt, R., Rackoff, G. N., Fitzsimmons-Craft, E. E., Rojas-Ashe, E., Barr Taylor, C., Funk, B., Eisenberg, D., Wilfley, D. E. & Newman, M. G., 02.04.2025, In: Psychological Medicine. 55, e106.Research output: Journal contributions › Journal articles › Research › peer-review
Open Access5 Citations (Scopus) -
Construct relation extraction from scientific papers: Is it automatable yet?
Funk, B. & Scharfenberger, J., 07.01.2025, Proceedings of the 58th Hawaii International Conference on System Sciences, HICSS 2025. Bui, T. X. (ed.). Honolulu: University of Hawaii at Manoa, p. 4675-4684 10 p. (Hawaii International Conference on System Sciences (HICSS); vol. 2025).Research output: Contributions to collected editions/works › Published abstract in conference proceedings › Research › peer-review
Open Access
Activities
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Developing an ontology for data science projects to facilitate the design process of a canvas
Thiée, L.-W. (Speaker)
21.02.2022 → 23.02.2022Activity: Talk or presentation › Conference Presentations › Research
File -
Fakultät MT allgemein (Organisational unit)
Funk, B. (Chair)
2022 → …Activity: Membership › Leuphana academic councils and committees › Leuphana Academic Committees
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„DATAx revised. Die Vermittlung digitaler Kompetenz im Leuphana Semester unter Berücksichtigung von Gender- und Diversityaspekten“
Hill, M. (Speaker) & van Deest, J. (Speaker)
09.03.2020Activity: Talk or presentation › Conference Presentations › Transfer
Press/Media
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What’s Hot: Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data
28.09.17
1 Media contribution
Press/Media
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Datasets
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sj-xlsx-3-dhj-10.1177_20552076241248920 - Supplemental material for Dataset size versus homogeneity: A machine learning study on pooling intervention data in e-mental health dropout predictions
Zantvoort, K. (Creator), Hentati Isacsson, N. (Creator), Funk, B. (Creator) & Kaldo, V. (Creator), SAGE Publications Inc., 16.05.2024
DOI: 10.25384/sage.25836893, https://sage.figshare.com/articles/dataset/sj-xlsx-3-dhj-10_1177_20552076241248920_-_Supplemental_material_for_Dataset_size_versus_homogeneity_A_machine_learning_study_on_pooling_intervention_data_in_e-mental_health_dropout_predictions/25836893
Dataset
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sj-xlsx-4-dhj-10.1177_20552076241248920 - Supplemental material for Dataset size versus homogeneity: A machine learning study on pooling intervention data in e-mental health dropout predictions
Zantvoort, K. (Creator), Funk, B. (Creator) & Kaldo, V. (Creator), SAGE Publications Inc., 2024
DOI: 10.1177/20552076241248920
Dataset
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sj-xlsx-3-dhj-10.1177_20552076241248920 - Supplemental material for Dataset size versus homogeneity: A machine learning study on pooling intervention data in e-mental health dropout predictions
Zantvoort, K. (Creator), Funk, B. (Creator) & Kaldo, V. (Creator), SAGE Publications Inc., 2024
DOI: 10.1177/20552076241248920
Dataset