In the following, I list some representative publications which best reflect my research interests. A more comprehensive list of publications can be found on my DBLP, Google Scholar, and ORCID profiles.

In my research, I'm particularly interested in the investigation of innovative applications of AI and analytics to real-world problems in various application domains, in particular air traffic management (ATM) and tax law but also dairy farming and social media communication, among others.

Using Genetic Algorithms for Privacy-Preserving Optimization of Multi-Objective Assignment Problems in Time-Critical Settings: An Application in Air Traffic Flow Management
Sebastian Gruber, Paul Feichtenschlager, Christoph G. Schuetz
Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) 2024.
https://doi.org/10.1145/3638529.3654128

Using Large Language Models and Law-Based Rules for the Analysis of VAT Chain-Transaction Cases in Austrian Tax Law
Marina Luketina, Lukas Knogler, Christoph G. Schuetz
Proceedings of the 1st Workshop on Bridging Hybrid Intelligence and the Semantic Web (HAIBRIDGE 2025).
https://ceur-ws.org/Vol-4093/Paper5hai.pdf

Choosing Response Strategies in Social Media Crisis Communication: An Evolutionary Game Theory Perspective
Lan Wang, Christoph G. Schuetz, Dahai Cai
Information & Management, Vol. 58, No. 6, 2021.
https://doi.org/10.1016/j.im.2020.103371

Building an active semantic data warehouse for precision dairy farming
Christoph G. Schuetz, Simon Schausberger, Michael Schrefl
Journal of Organizational Computing and Electronic Commerce, Vol. 28, No. 2, 2018.
https://doi.org/10.1080/10919392.2018.1444344

Semantics-based summarisation of ATM information: Managing information overload in pilot briefings using semantic data containers
Christoph G. Schuetz, Bernd Neumayr, Michael Schrefl, Eduard Gringinger, Scott Wilson
The Aeronautical Journal, Vol. 123, No. 1268, pp. 1639-1665, 2019.
https://doi.org/10.1017/aer.2019.74

Effective use of AI and analytics requires high-quality data, which must be provided by a data infrastructure that can cope with high volumes of a wide variety of data arriving at high velocity.

Knowledge Graph OLAP
Christoph G. Schuetz, Loris Bozzato, Bernd Neumayr, Michael Schrefl, Luciano Serafini
Semantic Web, Vol. 12, No. 4, pp. 649-683, 2021.
https://doi.org/10.3233/SW-200419

Providing packages of relevant ATM information: An ontology-based approach
Bernd Neumayr, Christoph G. Schuetz, Eduard Gringinger, Christoph Fabianek, Audun Vennesland, Michael Schrefl, Scott Wilson
Journal of Air Transport Management, Vol. 90, 2021.
https://doi.org/10.1016/j.jairtraman.2020.101937

A Cloud-Native Lakehouse Architecture for Using Knowledge Graphs in Aeronautical Information Management
Bashar Ahmad, Christoph G. Schuetz
Proceedings of the SESAR Innovation Days 2025.
https://www.sesarju.eu/sites/default/files/documents/sid/2025/papers/SIDs_2025_paper_86-final.pdf

Decision-makers must properly apply analytics solutions and correctly interpret the results to make good decisions. The representation of analytics-related knowledge facilitates proper use of analytics.

OLAP Patterns: A pattern-based approach to multidimensional data analysis
Ilko Kovacic, Christoph G. Schuetz, Bernd Neumayr, Michael Schrefl
Data & Knowledge Engineering, Vol. 138, 2022.
https://doi.org/10.1016/j.datak.2021.101948

Reference Modeling for Data Analysis: The BIRD Approach
Christoph G. Schuetz, Bernd Neumayr, Michael Schrefl, Thomas Neuböck
Journal of Cooperative Information Systems, Vol. 25, No. 2, 2016.
https://doi.org/10.1142/S0218843016500064

A Reference Process for Assessing the Reliability of Predictive Analytics Results
Simon Staudinger, Christoph G. Schuetz, Michael Schrefl
SN Computer Science, Vol. 5, No. 5, 2024.
https://doi.org/10.1007/s42979-024-02892-4

Knowledge graph support for descriptive business analytics
Simon Staudinger, Christoph G. Schuetz, Michael Schrefl, Thomas Neuböck
DECISION, Vol. 52, pp. 285-306, 2025.
https://doi.org/10.1007/s40622-025-00432-4

Multilevel modeling overcomes the dichotomy between class and object in the object-oriented modeling paradigm. Rather, multilevel models comprise clabjects, which are instances of classes but also themselves classes for other objects. One application of multilevel modeling that I'm particularly interested in is business process modeling, including the representation of analytics processes.

Dual deep modeling: multi-level modeling with dual potencies and its formalization in F-Logic
Bernd Neumayr, Christoph G. Schuetz, Manfred A. Jeusfeld, Michael Schrefl
Software and Systems Modeling, Vol. 17, No. 1, pp. 233-268, 2018.
https://doi.org/10.1007/s10270-016-0519-z

Multilevel Business Processes: Modeling and Data Analysis
Christoph G. Schuetz
Springer Vieweg, 2015.
https://doi.org/10.1007/978-3-658-11084-0

Dual Deep Modeling of Business Processes A Contribution to the Multi-Level Process Challenge
Bernd Neumayr, Christoph G. Schuetz, Michael Schrefl
Enterprise Modelling and Information Systems Architectures, Vol. 17, 2022.
https://doi.org/10.18417/emisa.17.7

Using Multilevel Business Artifacts for Knowledge Management in Analytics Projects
Simon Staudinger, Christoph G. Schuetz, Michael Schrefl
MODELS 2023 Companion, pp. 689-698, 2023.
https://doi.org/10.1109/MODELS-C59198.2023.00110