Christoph Singewald
Informatik
Knowledge Engineering.•Automated Reasoning and Decision-making Support.•"Atonomous" Intelligent Agents.
Wie unterscheidet der Mensch eine Vase von einem Glas? In einigen Fällen sind sich diese zwei Dinge doch sehr ähnlich.
Wie lernt der Mensch anhand weniger Beispiele und Erfahrungen? Wie treffen Menschen rationale und intuitive Entscheidungen?
Meinen ersten Computer – einen Commodore C64 – bekam ich mit 14. Seither begeistert mich die Entwicklung von Maschinen, die ausgestattet mit Wissen über unsere Welt eigenständig Entscheidungen treffen können. Seit meinem Informatikstudium beschäftigen mich nach einem kurzen Ausflug in die Computergrafik Themen der künstlichen Intelligenz und Graphentheorie. Ob maschinelles Lernen, automatisiertes Planen und Schließen oder Wissensrepräsentation, die Faszination blieb bisher ungebrochen und ich bemühe mich stets, in jedes Projekt meine Erfahrung und Fachexpertise einzubringen. Mit zunehmender Verbreitung der Algorithmen rücken auch deren gesellschaftliche und soziale Bedeutung sowie die Interaktion mit dem Menschen immer mehr in meinen Fokus.
Womit beschäftige ich mich?
Clowning
Als Clown möchte ich Menschen zum Lachen bringen und ihnen eine kurze Auszeit vom Alltag schenken.
Projects
A brief selection of successful projects I have been involved in
BOOST: AdaptaBle AutOmated Intelligence Gathering PrOceSses for Decision SupporT" – 2023/2024 FFG funded – in cooperation with the AIT Austrian Institute of Technology, Syncpoint GmbH for the Bundesministerium für Landesverteidigung
The aim of the project is to support analysts by automating individual steps in the intelligence process. The first step is to structure the collected data, the second step is to extract relevant information, and the final step is to derive suggestions and validate hypotheses through automated reasoning.
"PIONEER: InteroPerability and DIgitization Of INtelligencE GathEring Processes" – 2021/2022 FFG funded – in cooperation with the AIT Austrian Institute of Technology, Syncpoint GmbH for the Bundesministerium für Landesverteidigung
As a predecessor of the project BOOST the focus of this project was to support the intelligence analysts by automatically and manually structuring of the collected data and the automatically construction of the knowledge base using AI methods, supported by a dedicated user interface and digital tools. The knowledge base was used as a source for presenting the information in a network diagram as well as in time-based and geo-referenced images.
INTERPRETER - Interoperabilität im Katastrophenmanagement der nächsten Generation -2017/2018 - https://projekte.ffg.at/projekt/1850004 - https://www.ait.ac.at/themen/cooperative-digital-technologies/projekte/interpreter
Recognition of hand-drawn military symbols e.g MIL-STD-2525C for inclusion in the digital situation map.
Design and creation of a production rule system for the automated determination of the respective posting account based on various doman-specific parameters for Versicherungsanstalt öffentlich Bediensteter, Eisenbahnen und Bergbau (BVAEB)
Production rule system for Oracle database to derive daily closing prices of assets for AIM Software GmbH, Vienna.
Several projects for the game developer Greentube I.E.S. AG in the area of network layers, graphics and NPC agents.
ASP Solver in D and it's application using custom api e.g. SQL on various use cases e.g. route planing, simple medical diagnoses.
Private project for several internships at the technical university
Publications I contributed to
- Duro, Refiz & Weißenfeld, Axel & Singewald, Christoph & Andresel, Medina & Ignjatovic, Drazen & Siska, Veronika. (2024). Practical Approach for Processing and Fusion of Multimodal Data for Reconnaissance. 52-57. 10.1109/TechDefense63521.2024.10863240.
- Duro, R., Weißenfeld, A., Andresel, M., Siska, V., Ignjatovic, D., & Singewald, C. (2024). Automatic AI-Supported Information Extraction in Natural Hazards Reconnaissance. In P. Doucek, M. Sonntag, & L. Nedomova (Eds.), _32th Interdisciplinary Information Management Talks - IDIMT 2024: Changes to ICT, Management, and Business Processes through AI_ (Vol. 53, pp. 23-33) https://idimt.org/wp-content/uploads/2024/09/IDIMT-2024-proceedings.pdf
- Medina Andresel et al. (2024). Comparative Analysis of Open Source Knowledge Graph Systems for Military Reconnaissance - STO Meeting Proceedings - MP-IST-205-38 https://www.sto.nato.int/publications/STO%20Meeting%20Proceedings/STO-MP-IST-205/MP-IST-205-38.pdf (ast accessed 06/2025)
- Duro, R., Simon, R., & Singewald, C. (2023). AI-Enabled Services for Reconnaissance. _ERCIM NEWS- European Research Consortium for Informatics and Mathematics_, (132), 32-33. https://ercim-news.ercim.eu/en132/r-i/ai-enabled-services-for-reconnaissance
- R. Duro, M. Andresel, C. Singewald, V. Siska, A. Weißenfeld, and D. Ignjatović, “Boosting the automated Information Processing for Reconnaissance,” in 2023 IEEE International Workshop on Technologies for Defense and Security (TechDefense). Rome, Italy: IEEE, Nov. 2023, pp. 214–219.. 10.1109/TechDefense59795.2023.10380937.
- Duro, R., Ignjatovic, D., Lampert, J., Simon, R., & Singewald, C. (2022). Empowering reconnaissance processes through digitalization. In _30th Interdisciplinary Information Management Talks_ (pp. 145-152) https://doi.org/10.35011/IDIMT-2022
- Duro, Refiz & Simon, Rainer & Ignjatovic, Drazen & Lampert, Jasmin & Singewald, Christoph. (2022). TOWARDS DIGITALIZING RECONNAISSANCE PROCESSES WITH STAKEHOLDER REQUIREMENT ANALYSIS AND PERFORMANCE INDICATORS.
