TU Wien Informatics

Overview Professors Scientific Staff Administrative Staff Student Staff External Lecturers By Responsibilities By Committee By Name
Related
Guest Professors Honoraries Alumni (LinkedIn) #5qw

Tobias Geibinger

Projektass. Dipl.-Ing. / BSc

Tobias Geibinger

About

I am a recipient of a DOC Fellowship of the Austrian Academy of Sciences at the Institute of Logic and Computation at the TU Wien.

I work on notions of explainability in Answer-set Programming (ASP), especially for advanced language features and hybrid forms of ASP. Furthermore, I'm interested in logic in general and particularly in the context of AI.

Photo by Nadja Meister.

Role

Contact

2024W

2025S

 

  • Adaptive large-neighbourhood search for optimisation in answer-set programming / Eiter, T., Geibinger, T., Higuera Ruiz, N. N., Musliu, N., Oetsch, J., Pfliegler, D., & Stepanova, D. (2024). Adaptive large-neighbourhood search for optimisation in answer-set programming. Artificial Intelligence, 337, Article 104230. https://doi.org/10.1016/j.artint.2024.104230
  • Investigating constraint programming and hybrid methods for real world industrial test laboratory scheduling / Geibinger, T., Mischek, F., & Musliu, N. (2024). Investigating constraint programming and hybrid methods for real world industrial test laboratory scheduling. Journal of Scheduling. https://doi.org/10.1007/s10951-024-00821-0
    Project: ARTIS (2017–2025)
  • Parallel Empirical Evaluations: Resilience despite Concurrency / Fichte, J. K., Geibinger, T., Hecher, M., & Schlögel, M. (2024). Parallel Empirical Evaluations: Resilience despite Concurrency. In Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI 2024) (pp. 8004–8012). AAAI Press. https://doi.org/10.1609/aaai.v38i8.28638
  • Answer-Set Programming for Lexicographical Makespan Optimisation in Parallel Machine Scheduling - ADDENDUM / Eiter, T., Geibinger, T., Musliu, N., Oetsch, J., Skočovský, P., & Stepanova, D. (2024). Answer-Set Programming for Lexicographical Makespan Optimisation in Parallel Machine Scheduling - ADDENDUM. Theory and Practice of Logic Programming, 24(2). https://doi.org/10.1017/S1471068424000061
    Download: PDF (69.8 KB)
  • Explanations for Guess-and-Check ASP Encodings Using an LLM (Extended Abstract) / Geibinger, T., Kaminski, T., & Oetsch, J. (2024). Explanations for Guess-and-Check ASP Encodings Using an LLM (Extended Abstract). In Program TAASP. Workshop on Trends and Applications of Answer Set Programming (TAASP 2024), Klagenfurt, Austria. http://hdl.handle.net/20.500.12708/208540
  • Explaining Answer-Set Programs with Abstract Constraint Atoms (Extended Abstract) / Eiter, T., & Geibinger, T. (2023). Explaining Answer-Set Programs with Abstract Constraint Atoms (Extended Abstract). In Proceedings of the 2nd Workshop on Challenges and Adequacy Conditions for Logics in the New Age of Artificial Intelligence (ACLAI 2023) (pp. 1–6).
  • Contrastive Explanations for Answer-Set Programs / Eiter, T., Geibinger, T., & Oetsch, J. (2023). Contrastive Explanations for Answer-Set Programs. In Logics in Artificial Intelligence - 18th European Conference, JELIA 2023, Dresden, Germany, September 20-22, 2023, Proceedings (pp. 73–89). Springer. https://doi.org/10.1007/978-3-031-43619-2_6
  • Explainable Answer-set Programming / Geibinger, T. (2023). Explainable Answer-set Programming. In Proceedings ICLP 2023 (pp. 423–429). https://doi.org/10.4204/EPTCS.385.52
  • Explaining Answer-Set Programs with Abstract Constraint Atoms / Eiter, T., & Geibinger, T. (2023). Explaining Answer-Set Programs with Abstract Constraint Atoms. In Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI-23) (pp. 3193–3202). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2023/356
  • A Logic-based Approach to Contrastive Explainability for Neurosymbolic Visual Question Answering / Eiter, T., Geibinger, T., Higuera, N., & Oetsch, J. (2023). A Logic-based Approach to Contrastive Explainability for Neurosymbolic Visual Question Answering. In E. Elkind (Ed.), Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (pp. 3668–3676). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2023/408
  • Answer-Set Programming for Lexicographical Makespan Optimisation in Parallel Machine Scheduling / EITER, T., GEIBINGER, T., MUSLIU, N., OETSCH, J., SKOČOVSKÝ, P., & STEPANOVA, D. (2023). Answer-Set Programming for Lexicographical Makespan Optimisation in Parallel Machine Scheduling. Theory and Practice of Logic Programming, 23(6), 1281–1306. https://doi.org/10.1017/S1471068423000017
    Download: PDF (1020 KB)
  • ALASPO: An Adaptive Large-Neighbourhood ASP Optimiser (Extended Abstract) / Eiter, T., Geibinger, T., Higuera, N., Musliu, N., Oetsch, J., & Stepanova, D. (2022). ALASPO: An Adaptive Large-Neighbourhood ASP Optimiser (Extended Abstract). In Proceedings of the 5th Workshop on Trends and Applications of Answer Set Programming. 5th Workshop on Trends and Applications of Answer Set Programming, Vienna, Austria.
  • Large-Neighbourhood Search for Optimisation in Answer-Set Solving (Extended Abstract) / Eiter, T., Geibinger, T., Higuera Ruiz, N., Musliu, N., Oetsch, J., & Stepanova, D. (2022). Large-Neighbourhood Search for Optimisation in Answer-Set Solving (Extended Abstract). In Proceedings of the 38th International Conference on Logic Programming. 38th International Conference on Logic Programming, Haifa, Israel. Open Publishing Association. http://hdl.handle.net/20.500.12708/139851
  • A System for Automated Industrial Test Laboratory Scheduling / Danzinger, P., Geibinger, T., Janneau, D., Mischek, F., Musliu, N., & Poschalko, C. (2022). A System for Automated Industrial Test Laboratory Scheduling. ACM Transactions on Intelligent Systems and Technology. https://doi.org/10.1145/3546871
  • Large-Neighbourhood Search for Optimisation in Answer-Set Solving / Eiter, T., Geibinger, T., Higuera Ruiz, N., Musliu, N., Oetsch, J., & Stepanova, D. (2022). Large-Neighbourhood Search for Optimisation in Answer-Set Solving. In Proceedings of the 36th AAAI Conference on Artificial Intelligence (pp. 5616–5625). AAAI Press. https://doi.org/10.1609/aaai.v36i5.20502
  • An Open Challenge for Exact Job Scheduling with Reticle Batching in Photolithography / Eiter, T., Geibinger, T., Gisbrecht, A., Higuera Ruiz, N. N., Musliu, N., Oetsch, J., & Stepanova, D. (2022). An Open Challenge for Exact Job Scheduling with Reticle Batching in Photolithography. In KEPS 2022 Workshop on Knowledge Engineering for Planning and Scheduling. Workshop on Knowledge Engineering for Planning and Scheduling, Singapore. http://hdl.handle.net/20.500.12708/139763
  • ALASPO: An Adaptive Large-Neighbourhood ASP Optimiser / Eiter, T., Geibinger, T., Higuera, N., Musliu, N., Oetsch, J., & Stepanova, D. (2022). ALASPO: An Adaptive Large-Neighbourhood ASP Optimiser. In G. Kern-Isberner, G. Lackemeyer, & T. Meyer (Eds.), Proceedings of the 19th International Conference on Principles of Knowledge Representation and Reasoning — Applications and Systems (pp. 565–569). IJCAI Organization. https://doi.org/10.24963/kr.2022/58
  • Answer-Set Programming for Lexicographical Makespan Optimisation in Parallel Machine Scheduling / Eiter, T., Geibinger, T., Musliu, N., Oetsch, J., Skočovský, P., & Stepanova, D. (2021). Answer-Set Programming for Lexicographical Makespan Optimisation in Parallel Machine Scheduling. In Proceedings of the Eighteenth International Conference on Principles of Knowledge Representation and Reasoning. KR 2021 - 18th International Conference on Principles of Knowledge Representation and Reasoning, virtual event, Unknown. https://doi.org/10.24963/kr.2021/27
    Project: KIRAS-PrEMI (2019–2022)
  • Constraint Logic Programming for Real-World Test Laboratory Scheduling / Geibinger, T., Mischek, F., & Musliu, N. (2021). Constraint Logic Programming for Real-World Test Laboratory Scheduling. In 35th AAAI Conference on Artificial Intelligence (pp. 6358–6366). http://hdl.handle.net/20.500.12708/58591
    Project: ARTIS (2017–2025)
  • Physician Scheduling During a Pandemic / Geibinger, T., Kletzander, L., Krainz, M., Mischek, F., Musliu, N., & Winter, F. (2021). Physician Scheduling During a Pandemic. In Integration of Constraint Programming, Artificial Intelligence, and Operations Research (pp. 456–465). https://doi.org/10.1007/978-3-030-78230-6_29
    Project: ARTIS (2017–2025)
  • Sequent-Type Calculi for Systems of Nonmonotonic Paraconsistent Logics / Geibinger, T., & Tompits, H. (2020). Sequent-Type Calculi for Systems of Nonmonotonic Paraconsistent Logics. In Electronic Proceedings in Theoretical Computer Science (pp. 178–191). Electronic Proceedings in Theoretical Computer Science (EPTCS). https://doi.org/10.4204/eptcs.325.23
  • Solving the Test Laboratory Scheduling Problem with Variable Task Grouping / Danzinger, P., Geibinger, T., Mischek, F., & Musliu, N. (2020). Solving the Test Laboratory Scheduling Problem with Variable Task Grouping. In Proceedings of the Thirtieth International Conference on Automated Planning and Scheduling (pp. 357–365). http://hdl.handle.net/20.500.12708/58340
    Project: ARTIS (2017–2025)
  • Investigating constraint programming and hybrid answer-set solving for industrial test laboratory scheduling / Geibinger, T. (2020). Investigating constraint programming and hybrid answer-set solving for industrial test laboratory scheduling [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2020.73541
    Download: PDF (654 KB)
  • Investigating Constraint Programming for Real World Industrial Test Laboratory Scheduling / Geibinger, T., Mischek, F., & Musliu, N. (2019). Investigating Constraint Programming for Real World Industrial Test Laboratory Scheduling. In Integration of Constraint Programming, Artificial Intelligence, and Operations Research (pp. 304–319). Springer. https://doi.org/10.1007/978-3-030-19212-9_20
    Project: ARTIS (2017–2025)
  • Characterising Relativised Strong Equivalence with Projection for Non-ground Answer-Set Programs / Geibinger, T., & Tompits, H. (2019). Characterising Relativised Strong Equivalence with Projection for Non-ground Answer-Set Programs. In F. Calimeri, N. Leone, & M. Manna (Eds.), Logics in Artificial Intelligence: 16th European Conference, JELIA 2019 (pp. 542–558). Springer. https://doi.org/10.1007/978-3-030-19570-0_36
    Project: ARTIS (2017–2025)
  • ASAI Master Thesis Prize
    2023 / Austrian Society for Artificial Intelligence (ASAI) / Austria

Soon, this page will include additional information such as reference projects, activities as journal reviewer and editor, memberships in councils and committees, and other research activities.

Until then, please visit Tobias Geibinger’s research profile in TISS .