Committed to society.
Artificial Intelligence (AI) and Big Data are transforming how we understand the world, make decisions, and solve complex problems. We develop the scientific foundations that turn data into reliable knowledge.
Artificial Intelligence and Data Science (AI+DS) combines machine learning, data management, knowledge representation and reasoning, optimization, problem solving and search, information retrieval, recommender systems, natural language processing, computational science, and human-centered data analysis to develop AI systems that are scalable, trustworthy, and beneficial to society.
Our strong research networks including Bilateral AI (BilAI), the Center for Artificial Intelligence and Machine Learning (CAIML), alongside industry collaborations, connect fundamental research with real-world applications. We’re improving healthcare, engineering, mobility, and public services, developing systems for medical diagnosis, intelligent transport, and data-driven decision-making. All while advancing the fundamental methods behind the next generation of intelligent systems.
Powered by community.
AI+DS connects data to intelligence, pioneering research and technologies that shape how we understand and build the future.
Professors
Scientific Staff
Daniel Hofstätter D. Hofstätter
Computational Sustainability
PreDoc Researcher
Adrian Chroust A. Chroust
Knowledge-Based Systems
PreDoc Researcher
Selina Reinhard S. Reinhard
Software Engineering
PreDoc Researcher
Geoffrey Charles Joseph Sutcliffe G. Sutcliffe
Formal Methods in Systems Engineering
PostDoc Researcher
Marlene Gründel M. Gründel
Algorithms and Complexity
PreDoc Researcher
Thomas Neubauer T. Neubauer
Data Science
PostDoc Researcher
Manuel Sorge M. Sorge
Algorithms and Complexity
PostDoc Researcher
Sebastian Johannes Lüderssen S. Lüderssen
Machine Learning
PreDoc Researcher
Diana Marin D. Marin
Virtual and Augmented Reality
PostDoc Researcher
Katharina Flicker K. Flicker
Data Science
Office Services
Dedicated to excellence.
Big questions deserve high standards. Our award-winning research shows that we are pushing the limits. Here is what we have been working on.
Below is some of our recent work.
Want more?
Head over to our research unit pages!
Recent Projects
- 2026 – 2032 / Vienna Science and Technology Fund (WWTF)
- 2025 – 2032 / Vienna Science and Technology Fund (WWTF) / Publications (3)
- 2025 – 2031 / European Commission
- 2026 – 2030 / Austrian Science Fund (FWF)
- 2024 – 2030 / Vienna Science and Technology Fund (WWTF) / Publications (7)
- 2026 – 2029 / Vienna Science and Technology Fund (WWTF) / Publications (4)
- 2025 – 2029 / European Commission / Publications (5)
- 2024 – 2029 / Austrian Science Fund (FWF) / Publications (28)
- 2026 – 2028 / Austrian Exchange Service (OeAD)
- 2026 – 2028 / Austrian Research Promotion Agency (FFG)
- 2025 – 2028 / Wirtschaftsuniversität Wien
- 2024 – 2027 / Austrian Science Fund (FWF) / Publications (3)
- 2023 – 2027 / AXA
- 2023 – 2027 / European Commission / Website
- 2025 – 2026 / Austrian Exchange Service (OeAD) / Publication
- 2025 – 2026 / Austrian Exchange Service (OeAD)
- 2025 – 2026 / Austrian Exchange Service (OeAD)
- 2024 – 2025 / CONENGA Engineers GmbH
- 2017 – 2025 / Christian Doppler Research Association (CDG) / Website / Publications (70)
- 2021 – 2024 / Austrian Research Promotion Agency (FFG)
Recent Publications
- Cheng, Z., Dai, W., Sun, J., Lukasiewicz, T. (2027). HoloCoT: Holographic Chain-of-Thought via Orthogonal Subspace Anchoring for Persistent Long-Horizon Reasoning. In M. Ceci, D. Kocev, A. Monreale, C. Vens, P. Flach, G. Manco, M. Spiliopoulou, E. Masciari (Eds.), Machine Learning and Knowledge Discovery in Databases. Research Track European Conference, ECML PKDD 2026, Naples, Italy, September 7–11, 2026, Proceedings, Part IV (pp. 107–122). Springer.
- Fraboulet, K., Al-Eryani, A., Heinzelmann, S., Kauch, A., Andergassen, S. (2026). Multiloop functional renormalization group from single bosons. Physical Review Research (PRResearch), 8(4), Article 043139. Peer-reviewed.DOI: 10.1103/k1l3-czq7
- Cheng, Z., Dai, W., Sun, J., Lukasiewicz, T. (2026). Imbuing Large Language Models with Bidirectional Logic for Robust Chain Repair. In Machine Learning and Knowledge Discovery in Databases. Research Track : European Conference, ECML PKDD 2026, Naples, Italy, September 7–11, 2026, Proceedings, Part V (pp. 595–610). Springer. Peer-reviewed.
- Xu, Z., Wang, Z., Liu, J., Li, B., Ma, X., Zhan, Y., Yang, R., Lukasiewicz, T. (2026). HGR-DiffSeg: Hybrid-guided robust diffusion model for medical image segmentation. Biomedical Signal Processing and Control, 123(B), Article 110591. Peer-reviewed.
- Kumar, G. K., Perlitz, Y., Lammie, C., Giovannini, A., Hose, K. (2026). DataKernelBench: Can LLMs Optimize Database Queries on GPUs? arXiv.DOI: 10.48550/ARXIV.2608.25061 / Project: ARMADA
- Gortworst, B., Okulmus, C., Ortiz, M., Turhan, A.-Y. (2026). Shapes from Examples: Foundations of Shape Learning in Recursive SHACL. arXiv.
- Winter, F. (2026). A Two-Stage Constraint Programming Approach for Artificial Teeth Scheduling. In 32nd International Conference on Principles and Practice of Constraint Programming (pp. 1–23). Schloss Dagstuhl – Leibniz-Zentrum für Informatik. Peer-reviewed.
- Ningtyas, A. M., Herwanto, G. B., Sari, Y., Putri, R. A., Kovacevic, F., El-Ebshihy, A., Arzt, V., Piroi, F. (2026). AnnoHID: LLM-Assisted Annotation Framework for Low-Resource Medical Texts. In G. Durrett P. Jian (Eds.), Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations) (pp. 683–691). Association for Computational Linguistics. Peer-reviewed.DOI: 10.18653/v1/2026.acl-demo.67 / Project: ANOHID
- Ganepola, K., Jakubowski, M., Hose, K. (2026). Computing Why-Provenance for Property Graph Queries. Proceedings of the VLDB Endowment, 19(11), 3552–3564. Peer-reviewed.
- Frühwirth, L., Einspieler, C., Musliu, N., Winter, F. (2026). GPMS: A Generalized Parallel Machine Scheduling Framework with Rich Temporal and Resource Constraints. In Proceedings of the Thirty-Sixth International Conference on Automated Planning and Scheduling (pp. 490–499). AAAI Press. Peer-reviewed.
- Jakubowski, M., Tomaszuk, D., Hose, K. (2026). A Community Survey on {SHACL} and ShEx: Briding Gaps in RDF Validation. arXiv.
- Akter, Y. A., Abello, A., Jovanovic, P., Sagi, T., Hose, K. (2026). Exploring the Landscape of Data Fusion. In G. DEJAEGERE, A. Abelló, K. Torp, A. Simitsis (Eds.), Data Engineering for Data Science (pp. 33–62). Springer Cham. Peer-reviewed.
- Kapenekakis, A., Dell’Aglio, D., Bøgsted, M., Garofalakis, M., Hose, K. (2026). Scalable and Privacy-Aware Relational Data Synthesis. In G. DEJAEGERE, A. Abelló, K. Torp, A. Simitsis (Eds.), Data Engineering for Data Science (pp. 63–77). Springer Cham. Peer-reviewed.
- Nematov, I., Sacharidis, D., Hose, K., Sagi, T. (2026). Example-Based Explainability in Machine Learning. In G. DEJAEGERE, A. Abelló, K. Torp, A. Simitsis (Eds.), Data Engineering for Data Science (pp. 215–234). Springer Cham. Peer-reviewed.
- Günes, H. H., Jovanovik, M., Hose, K. (2026). MetriKG: Profiling Static and Evolving Knowledge Graphs. In H. Hacid Y. Maarek (Eds.), WWW Companion ’26: Companion Proceedings of the ACM Web Conference 2026 (pp. 200–203). Association for Computing Machinery. Peer-reviewed.
- Pelgrin, O., Taelman, R., Galárraga, L., Hose, K. (2026). Expressive Querying and Scalable Management of Large RDF Archives. Semantic Web, 17(3). Peer-reviewed.
- Xu, Z., Liu, Y., Yuan, D., Li, B., Liu, W., Lukasiewicz, T. (2026). You Need Glimpse Before Segmentation: Stochastic Detector-Actor-Critic for Medical Image Segmentation. IEEE Journal of Biomedical and Health Informatics, 30(5), 4186–4199. Peer-reviewed.
- Wang, X., Wang, R., Lukasiewicz, T., Xu, Z. (2026). AMLP: Adjustable Masking Lesion Patches for Self-Supervised Medical Image Segmentation. IEEE Transactions on Medical Imaging, 45(5), 1730–1746. Peer-reviewed.
- Dolci, T., Jovanovik, M., Hose, K. (2026). Towards LLM-KG Symbiosis for Reducing Factual Hallucinations. In A. Krause J. F. Pimentel (Eds.), EDBT/ICDT 2026 Workshops : Proceedings of the Workshops of the EDBT/ICDT 2026 Joint Conference co-located with the EDBT/ICDT 2026 Joint Conference. CEUR-WS.org. Peer-reviewed.
- Jovanovik, M., Vecovska, M., Jakubowski, M., Hose, K. (2026). RDFGraphGen: An RDF Graph Generator Based on SHACL Shapes. In Knowledge Graphs : 14th International Joint Conference, IJCKG 2025, Heraklion, Crete, Greece, October 15–17, 2025, Proceedings (pp. 111–125). Springer. Peer-reviewed.DOI: 10.1007/978-981-95-5009-8_8 / Project: TARGET
Recent Presentations
- Andergassen, S., Hepp, S., Zabielski, D., Springer, D. (2026, September 22). Machine learning latent orders from the two-particle vertex [Conference Presentation]. OePG-CMD JOINT MEETING 2026, Graz, Austria. Invited.HDL: 20.500.12708/231338
- Domizio, F., Al-Eryani, A., Andergassen, S., Scherer, M. M. (2026, September 21). Unbiased functional renormalization group study of Su-Schrieffer-Heeger phonons in the two-dimensional Hubbard model [Poster Presentation]. OEPG-CMD JOINT MEETING 2026, Graz, Austria.HDL: 20.500.12708/231745
- Eiter, T., Nießen, T., Soldà, D. (2026, September 8). SAT Modulo Well-Founded Semantics: Extended Abstract [Conference Presentation]. 18th International Conference on Logic Programming and Non-monotonic Reasoning (LPNMR 2026), Austria.
- Schrott, J. (2026, September 4). Graph-Native Normalization : Reducing Redundancy in Labeled Property Graphs [Presentation]. Twenty-First GDC TUC Meeting, Boston, United States of America (the).
- Kletzander, L. (2026, August 27). Multi-Contract Integrated Shift Design and Rostering [Conference Presentation]. The 15th Conference on the Practice and Theory of Automated Timetabling (PATAT 2026), Nottingham, United Kingdom of Great Britain and Northern Ireland (the).HDL: 20.500.12708/230853
- Andergassen, S. (2026, July 23). Intertwined fluctuations and isotope effects in the Hubbard-Holstein model [Conference Presentation]. M2S 2026, Stuttgart, Germany.HDL: 20.500.12708/229575
- Gjergji, I., Kletzander, L., Musliu, N. (2026, July 16). Hyper-heuristics for the capacitated p-median problem [Conference Presentation]. The 24th Conference of the International Federation of Operational Research Societies (IFORS 2026), Vienna, Austria.HDL: 20.500.12708/231635 / Project: BioLog
- Zihan, W. S., Delrocq, A., Gerstner, W., Bellec, G. (2026, July 7). Can local learning match self-supervised backpropagation? [Poster Presentation]. Forty-Third International Conference on Machine Learning (ICML 2026), Seoul, Korea (the Republic of).HDL: 20.500.12708/232177
- Patricolo, M., Vilardi, D., Andergassen, S., Forni, P. (2026, March 16). Functional renormalization group treatment of the spiral phase [Conference Presentation]. APS Global Physics Summit 2026, United States of America (the).HDL: 20.500.12708/227105
- Fraboulet, K., Al-Eryani, A., Gievers, M. S., Heinzelmann, S., Krien, F., Andergassen, S. (2026, March 9). Competing instabilities for models with non-local and retarded interactions: a functional renormalization group perspective [Conference Presentation]. DPG Spring Meeting of the Condensed Matter Section, Dresden, Germany.HDL: 20.500.12708/227076
- Szeider, S. (2025, December 15). Selbstreflektierende KI [Presentation]. Digitaler Humanismus Salon 2025, Wien, Austria.HDL: 20.500.12708/225760
- Patricolo, M., Forni, P., Andergassen, S., Vilardi, D. (2025, December 8). Functional Renormalization Group Treatment of the Spiral Phase [Poster Presentation]. Advanced School and Conference on Quantum Matter 2025, Triest, Italy.HDL: 20.500.12708/222559
- Lavrinovics, E., Biswas, R., Hose, K., Bjerva, J. (2025, December 5). MultiHal: MultiLingual Dataset for Knowledge-Graph Grounded Evaluation of LLM Hallucinations [Poster Presentation]. EurIPS 2025, Kopenhagen, Denmark.HDL: 20.500.12708/222139
- Gjergji, I., Kletzander, L., Bierlee, H., Musliu, N., Stuckey, P. J. (2025, November 10). A Consecutive Flight Leg Model for the Aircraft Maintenance Routing Problem [Conference Presentation]. Knowledge Engineering for Planning and Scheduling (KEPS 2025), Melbourne, Australia.HDL: 20.500.12708/225746
- Katja Hose. (2025, October 15). Sharp Edges in a Fuzzy World: Knowledge Graphs and LLMs [Keynote Presentation]. 14th International Joint Conference on Knowledge Graphs, Iraklion, Greece.HDL: 20.500.12708/221598
- Gjergji, I., Kletzander, L., Musliu, N., Schaerf, A., Smith-Miles, K. (2025, October 1). Investigating the Capacitated Facility Location Problem with Customer Incompatibilities Using Instance Space Analysis [Presentation]. Middle-European Conference on Applied Theoretical Computer Science, Slovenia.HDL: 20.500.12708/225683
- Indri, P., Drucks, T., Gärtner, T. (2025, September 15). Private and Expressive Graph Representations [Conference Presentation]. 22nd International Workshop on Mining and Learning with Graphs, Porto, Portugal.HDL: 20.500.12708/224052
- Sandrock, C., Lüderssen, S. J., Thiessen, M., Gärtner, T. (2025, September 15). Efficient Minimization of Peakless Functions on Bounded-degree Graphs [Presentation]. 22nd International Workshop on Mining and Learning with Graphs, Porto, Portugal.HDL: 20.500.12708/225752
- Kletzander, L. (2025, September 11). Integrating Column Generation and Large Neighborhood Search [Presentation]. Dagstuhl Seminar 25371 : Interactions in Constraint Optimization, Wadern, Germany.HDL: 20.500.12708/224516
- Hepp, S., Andergassen, S., Springer, D. (2025, August 20). Machine Learning for Quantum Many-Body Physics: Efficient Representation of Vertex Functions [Poster Presentation]. Joint Annual Meeting of the Austrian and Swiss Physical Society (ÖPG and SPS 2025), Wien, Austria.HDL: 20.500.12708/218509
Recent Theses
- Gaebel, Y. (2026). Strategic transferability in poverty map inference [Diploma Thesis, Technische Universität Wien]. reposiTUm.DOI: 10.34726/hss.2026.126764 / Download: PDF
- Süss, M. (2026). Faithfulness of natural language explanations for vision language models : an automated test framework [Diploma Thesis, Technische Universität Wien]. reposiTUm.DOI: 10.34726/hss.2026.132363 / Download: PDF
- Oberbacher, M. (2026). Automatic pipe routing approach for HVAC systems in complex building architectures [Diploma Thesis, Technische Universität Wien]. reposiTUm.
- Hepp, S. (2026). Machine learning for quantum many-body physics : efficient representation of vertex functions [Diploma Thesis, Technische Universität Wien]. reposiTUm.DOI: 10.34726/hss.2026.128261 / Download: PDF
- Sula, J. (2026). Faithful attention attribution in vision transformers for chest X-ray interpretation [Diploma Thesis, Technische Universität Wien]. reposiTUm.DOI: 10.34726/hss.2026.132361 / Download: PDF
- Brasoveanu, D.-A. (2026). Extending graph neural networks with global features [Diploma Thesis]. reposiTUm.DOI: 10.34726/hss.2026.120129 / Download: PDF
- Dasovic, I. (2026). Aggregation techniques in federated learning under differential privacy constraints [Diploma Thesis, Technische Universität Wien]. reposiTUm.DOI: 10.34726/hss.2026.131806 / Download: PDF
- Höller, M. (2026). Database replication with persistent citation functionality [Diploma Thesis, Technische Universität Wien]. reposiTUm.DOI: 10.34726/hss.2026.131801 / Download: PDF
- Mexhuani, B. (2026). Hierarchical time series forecasting of daily ambulance demand [Diploma Thesis, Technische Universität Wien]. reposiTUm.DOI: 10.34726/hss.2026.135562 / Download: PDF
- Hecht, S. G. (2026). A fair multi-stakeholder job market recommender leveraging personality [Diploma Thesis, Technische Universität Wien]. reposiTUm.DOI: 10.34726/hss.2026.80420 / Download: PDF
- Böhm, J. (2026). Message passing on the edge : going beyond triangles [Diploma Thesis, Technische Universität Wien]. reposiTUm.DOI: 10.34726/hss.2026.137416 / Download: PDF
- Melnychyn, O. (2026). Federated learning in edge computing settings in medical domain [Diploma Thesis, Technische Universität Wien]. reposiTUm.DOI: 10.34726/hss.2026.129963 / Download: PDF
- Sakka, M. A. (2026). An inquiry into the nature of predictive model classes and the forecasting of corporate insolvency [Diploma Thesis, Technische Universität Wien]. reposiTUm.DOI: 10.34726/hss.2026.137286 / Download: PDF
- Elebshihy, A. M. (2026). Identifying and Representing Knowledge Delta in Scientific Literature [Dissertation, Technische Universität Wien]. reposiTUm.DOI: 10.34726/hss.2026.140233 / Download: PDF
- Maksan, T. (2026). Enhancing privacy in machine learning through teacher-guided synthetic data generation : a modified PATE framework [Diploma Thesis, Technische Universität Wien]. reposiTUm.DOI: 10.34726/hss.2026.133330 / Download: PDF
- Kravchenko, O. (2026). Spike sorting of brain signals with deep learning [Diploma Thesis, Technische Universität Wien]. reposiTUm.DOI: 10.34726/hss.2026.134564 / Download: PDF
- Roth, S. (2026). Efficient end-to-end brain-to-text decoding via neural pretraining [Diploma Thesis, Technische Universität Wien]. reposiTUm.DOI: 10.34726/hss.2026.141781 / Download: PDF
- Lahnsteiner, P. (2026). Relational database preservation [Diploma Thesis, Technische Universität Wien]. reposiTUm.DOI: 10.34726/hss.2026.122572 / Download: PDF
- Kanev, K. (2026). AI in manufacturing : Developing a Federated Machine Learning approach for production machines [Diploma Thesis, Technische Universität Wien]. reposiTUm.
- Prisiazhniuk, A. (2026). Project partner extraction from research contracts [Diploma Thesis, Technische Universität Wien]. reposiTUm.DOI: 10.34726/hss.2026.132974 / Download: PDF
We shape the future.
Artificial Intelligence is evolving. We aim to shape AI’s evolution so it strengthens society and safeguards what matters. Reinforced by collaborations with Digital Humanism, we’re not only focussing on how AI solutions work, but on their societal and economic effects. With this commitment, we want to strengthen Europe’s digital sovereignty, and further expand our collective capacity to understand and shape the AI technologies that will define our future.
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