Publications
Unleashing the Unpredictable: Generating Context-Driven Synthetic Black Swans
Abdel Khaliq, Lotfy; Janzen, Sabine; and Maass, Wolfgang
ICIS 2024
Introduces a framework for generating synthetic black swan events to model unpredictable crises.
A Proposal for Physics-Informed Quantum Graph Neural Networks for Simulating Laser Cutting Processes
Ruhi, Z. M., Stein, H., & Maass, W.
INFORMATIK 2023. Gesellschaft für Informatik, Bonn. {KI-basiertes} Management und Optimierung komplexer Systeme (MOC). Berlin. 26.-30. September 2023
This paper presents a novel approach for using quantum graph neural networks in simulating laser cutting processes.
ADA: Automatic Data Annotation for Data Ecosystems
Gdanitz, N., Janzen, S., Stein, H., Harig, A., Maass, W.
In: Proceedings of the ISWC 2023 Posters, Demos and Industry Tracks. International Semantic Web Conference (ISWC-2023), located at 22nd International Semantic Web Conference, November 6-10, Athens, Greece, Springer, 2023
ADA introduces a novel approach for automatic data annotation in data ecosystems.
Anticipating Energy-driven Crises in Process Industry by AI-based Scenario Planning
Janzen, S., Gdanitz, N., Khaliq, L., Munir, T., Franzius, C., Maass, W.
In: HICSS 56/23. Hawaii International Conference on System Sciences (HICSS-2023), January 3-6, Maui, Hawaii, USA, HICSS, 2023
AI-based scenario planning to predict and address energy crises in process industries.
Cascading Scenario Technique Enabling Automated And Situation-based Crisis Management
Leachu, S., Janßen, J., Gdanitz, N., Kirchhöfer, M., Janzen, S., Stich, V.
In Proceedings of the Conference on Production Systems and Logistics. Conference on Production Systems and Logistics (CPSL-2023), February 28 – March 3, Santiago De Querétaro, Mexico, Publish.Ing, 2023
Introduces the cascading scenario technique for automating crisis management in production systems.
Conceptual Alignment Method
Maass, W., Castellanos, A., Tremblay, M., Lukyanenko, R., Storey, V. C., Almeida, J. S.
In Proceedings of the Twenty-ninth Americas Conference on Information Systems. Americas Conference on Information Systems (AMCIS 2023) Panama, 2023
Explores a conceptual alignment method for enhancing data integration and interoperability.
Decoding Resilience: A Graph-based Approach for Organizational Resilience Assessment
Janzen, S., Harig, A., Gdanitz, N., Stein, H., Öksüz-Köster, N., Maass, W.
Conference Proceedings of International Conference on Conceptual Modeling (ER 2023), CEUR-WS.org, 11/2023
This paper proposes a graph-based method for assessing organizational resilience.
Modelling Metabolism Pathways using Graph Representation Learning for Fraud Detection in Sports
Rahman, M.R., Hussain, M., Piper, T., Geyer, H., Equey, T., Baume, N., Aikin, R., Maass, W.
In Proceedings of IEEE International Conference on Digital Health, (ICDH 23), July 2-8, Chicago, Illinois, USA, 2023
This paper presents a novel graph representation learning approach for detecting fraudulent behaviors in sports.
Monetary Valuation of Data in the Context of Accounting
Stein, H., Maass, W.
Daniel Trauth; Thomas Bergs; Wolfgang Prinz. The Monetization of Technical Data: Innovations from Industry and Research. Pages 103-116, ISBN 978-3-662-66509-1, Springer Berlin Heidelberg, Berlin, Heidelberg, 2023
Discusses approaches for monetary valuation of data assets in accounting.
PAIRS – Privacy-Aware, Intelligent and Resilient Crisis Management
Janzen, S., Ahiagble, A.P., Abdel Khaliq, L., Gdanitz, N., Saxena, P., Mithare, P., Skrytskyi, D., Maass, W.
In: Conference Proceedings (Vol. 2). International Conference on Conceptual Modeling (ER-2023)
PAIRS is a framework for intelligent and privacy-aware crisis management.
POWOP: Weather-based Power Outage Prediction
Gdanitz, N., Abdel Khaliq, L., Ahiagble, A.P., Janzen, S., Maass, W.
In: IntelliSys 2023. Intelligent Systems Conference, September 7-8, Amsterdam, Netherlands. SAI IntelliSys 2023
Presents a framework for predicting power outages using weather data and intelligent systems.
PRScalc, a privacy-preserving calculation of raw polygenic risk scores from direct-to-consumer genomics data
Sandoval, L., Jafri, S., Balasubramanian, J. B., Bhawsar, P., Edelson, J. L., Martins, Y., Maass, W., Chanock, S. J., Garcia-Closas, M., & Almeida, J. S.
Bioinformatics Advances, 3(1), vbad145
PRScalc introduces a privacy-preserving approach for polygenic risk score calculations.
QUASIM: Quantum Computing Enhanced Service Ecosystem for Simulation in Manufacturing
Agrawal, A., Stein, H., Xu, S., Janzen, S., Maass, W.
Conference Proceedings of International Conference on Conceptual Modeling (ER 2023), Project Exhibitions, CEUR-WS.org, 11/2023
QUASIM explores the use of quantum computing to enhance service ecosystems for manufacturing simulations.
SNOOP Method: Faithfulness of Text Summarizations for Single Nucleotide Polymorphisms
Maass, W., Agnes, C.K., Rahman, M.R., Almeida, J.S.
2nd Symposium on Human Partnership with Medical AI: Design, Operationalization, and Ethics at the Association for the Advancement of Artificial Intelligence (AAAI) Summer Symposium 2023, Singapore
SNOOP method evaluates the faithfulness of text summarizations for genetic variations.
Tackling Non-Transparency-Identification of hidden problems in component-based supply chains
Janzen, S., Baer, S., Ahiagble, A.P., Maass, W.
In Proceedings of 20th International Conference on Information Systems for Crisis Response and Management (ISCRAM). International Conference on Information Systems for Crisis Response and Management (ISCRAM), May 28-31, Omaha, Nebraska, USA, ISCRAM digital library
Presents methods for identifying hidden issues in component-based supply chains to improve transparency.