Markus Nissl
Projektass. Dipl.-Ing. / BSc
Role
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PreDoc Researcher
Databases and Artificial Intelligence, E192-02
Courses
Publications
Note: Due to the rollout of TU Wien’s new publication database, the list below may be slightly outdated. Once the migration is complete, everything will be up to date again.
- Monotonic Aggregation for Temporal Datalog / Bellomarini, L., Nissl, M., & Sallinger, E. (2021). Monotonic Aggregation for Temporal Datalog. In Proceedings of the 15th International Rule Challenge, 7th Industry Track, and 5th Doctoral Consortium @ RuleML+RR 2021 co-located with 17th Reasoning Web Summer School {(RW} 2021) and 13th DecisionCAMP 2021 as part of Declarative {AI} 2021, Leuven, Belgium (virtual due to Covid-19 pandemic), 8 - 15 September, 2021} (pp. 1–23). http://hdl.handle.net/20.500.12708/58594 / Project: KnowledgeGraph
- Towards Cross-Blockchain Smart Contracts / Nissl, M., Sallinger, E., Schulte, S., & Borkowski, M. (2021). Towards Cross-Blockchain Smart Contracts. In 2021 IEEE International Conference on Decentralized Applications and Infrastructures (DAPPS). DAPPS 2021 - International Conference on Decentralized Applications and Infrastructures, online event, International. https://doi.org/10.1109/dapps52256.2021.00015 / Project: KnowledgeGraph
- Knowledge Graphs: Detection of Outdated News / Ferranti, N., Krickl, A., & Nissl, M. (2021). Knowledge Graphs: Detection of Outdated News. In Proceedings of the {ISWC} 2021 Posters, Demos and Industry Tracks: From Novel Ideas to Industrial Practice co-located with 20th International Semantic Web Conference {(ISWC} 2021), Virtual Conference, October 24-28, 2021}, (pp. 1–5). http://hdl.handle.net/20.500.12708/55638 / Project: KnowledgeGraph
- Rule-based Blockchain Knowledge Graphs: Declarative {AI} for Solving Industrial Blockchain Challenges / Bellomarini, L., Galano, G., Nissl, M., & Sallinger, E. (2021). Rule-based Blockchain Knowledge Graphs: Declarative {AI} for Solving Industrial Blockchain Challenges. In Proceedings of the 15th International Rule Challenge, 7th Industry Track, and 5th Doctoral Consortium @ RuleML+RR 2021 co-located with 17th Reasoning Web Summer School {(RW} 2021) and 13th DecisionCAMP 2021 as part of Declarative {AI} 2021, Leuven, Belgium (virtual due to Covid-19 pandemic), 8 - 15 September, 2021} (pp. 1–16). http://hdl.handle.net/20.500.12708/55637 / Project: KnowledgeGraph
- Reasoning on Company Takeovers during the COVID-19 Crisis with Knowledge Graphs / Bellomarini, L., Benedetti, M., Ceri, S., Laurendi, R., Magnanimi, D., Nissl, M., & Sallinger, E. (2020). Reasoning on Company Takeovers during the COVID-19 Crisis with Knowledge Graphs. In roceedings of the 14th International Rule Challenge, 4th Doctoral Consortium, and 6th Industry Track @ RuleML+RR 2020 co-located with 16th Reasoning Web Summer School {(RW} 2020) 12th DecisionCAMP 2020 as part of Declarative {AI} 2020, Oslo, Norway (virtual due to Covid-19 pandemic), 29 June - 1 July, 2020 (pp. 145–156). http://hdl.handle.net/20.500.12708/55579 / Project: KnowledgeGraph
- Blockchains as Knowledge Graphs - Blockchains for Knowledge Graphs (Vision Paper) / Bellomarini, L., Nissl, M., & Sallinger, E. (2020). Blockchains as Knowledge Graphs - Blockchains for Knowledge Graphs (Vision Paper). In Proceedings of the International Workshop on Knowledge Representation and Representation Learning co-located with the 24th European Conference on Artificial Intelligence {(ECAI} 2020), Virtual Event, September, 2020 (pp. 43–51). http://hdl.handle.net/20.500.12708/58743 / Project: KnowledgeGraph
- Cross-blockchain smart contracts : invoking smart contracts across blockchains / Nissl, M. (2019). Cross-blockchain smart contracts : invoking smart contracts across blockchains [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2019.64606
Supervisions
Note: Due to the rollout of TU Wien’s new publication database, the list below may be slightly outdated. Once the migration is complete, everything will be up to date again.
- VT-KGNN: A Valid time knowledge graph neural network / Auer, A. (2022). VT-KGNN: A Valid time knowledge graph neural network [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2022.101061
- Reasoning in financial knowledge graphs : Making Industry sectors accessible to AI / Schüller, M. (2022). Reasoning in financial knowledge graphs : Making Industry sectors accessible to AI [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2022.98942
- Foundations of knowledge graphs: Complexity of arithmetic in vadalog / Berent, L. (2021). Foundations of knowledge graphs: Complexity of arithmetic in vadalog [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2021.93121
- Recursive rule injection in knowledge graphs : Exploiting logical knowledge in machine learning / Wagner, F. K. M. (2021). Recursive rule injection in knowledge graphs : Exploiting logical knowledge in machine learning [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2021.85260