
Databases & Artificial Intelligence Group @TU Wien
@dbai_tuwien
Databases and Artificial Intelligence Group | Institute of Logic and Computation | Faculty of Informatics | TU Wien
ID: 1771592339984670720
https://dbai.tuwien.ac.at 23-03-2024 17:40:52
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🚨 Full Episode! Shellie Boudreau, PhD interviews Katja Hose about perseverance, the challenges of interdisciplinary collaboration, the pace of progress in computer science, and the integration of diverse datasets. Watch below here! #NobleBlocks #DeSci #computerscience


The SIGMOD/PODS 2025 Programming Contest goes into another round. We (Bo Tang, Tilmann Rabl, and myself) just published the timeline and task overview: sigmod-contest-2025.github.io/index.html Thanks to Carlo Curino and Microsoft for the continued support.




A postcard from Lausanne - I just returned from the Applied Machine Learning Days (AMLD) at EPFL. Thanks to Thaleia Dimitra Doudali and Pamela Delgado for organizing the "AI in Data and Computer Systems" session - it was a pleasure.


In a recent Schloss Dagstuhl seminar we developed a research roadmap towards Computer-Using Personal Agents, which automate complex tasks like today's Computer-Using Agents, but include context via controlled access to personal knowledge graphs. Our vision paper: openaccess.city.ac.uk/id/eprint/34788


#EDBT2025 has just officially started with the opening ceremony and a warm welcome by the general chairs, Oscar Romero and Anna Queralt , and the program chairs, Bettina Kemme and Alkis Simitsis. Looking forward to enjoying the program during the next couple of days.


Proudly watching Martin Pekar presenting "Fantastic Tables and Where to Find Them: Table Search in Semantic Data Lakes" at #EDBT2025 authors: Martin Pekár, Aristotelis Leventidis, M. Lissandrini, Laura Di Rocco, Renée J. Miller, Katja Hose openproceedings.org/2025/conf/edbt…






Honored to receive the IFIP TC2 Manfred Paul Award (2024) with Kashif Rabbani & M. Lissandrini for our VLDB 2022 paper on generating #SHACL shapes from large knowledge graphs. Scales to billions of triples, mining meaningful patterns using support & confidence. vldb.org/pvldb/vol16/p1…
