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Data Science Chair

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About Us

The Data Science Chair (formerly DMIR Research Group) is a highly interdisciplinary group of researchers led by Prof. Andreas Hotho. We are active in machine learning research with applications in multiple domains, namely environmental sensing, natural language processing, recommendation, semantic web and fraud detection.

News

Bienen für das Digitalministerium

Jetzt brummt es auch auf dem Dach des Bayerischen Digitalministeriums! Im Rahmen des von Prof. Dr. Andreas Hotho mitbetreuten we4bee-Projekts wurde nun ein digitale überwachter Bienenstock mit einer Menge neuer Untermieter auf dem Dach des Ministeriums aufgestellt.

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Our Paper "Self-Supervised Multi-Task Pretraining Improves Image Aesthetic Assessment" got accepted

Our paper "Self-Supervised Multi-Task Pretraining Improves Image Aesthetic Assessment" got accepted for publication at "New Trends in Image Restoration and Enhancement workshop" (NTIRE) at CVPR 2021.

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Grünes Licht für Neubau

Der erste Neubau für das Forschungszentrum „Künstliche Intelligenz und Data Science“ CAIDAS der Uni Würzburg ist in Sicht. Der Freistaat Bayern hat dafür grünes Licht gegeben und stellt Mittel bereit.

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Deep Learning for Climate Model Output Statistics @ EGU21

Our group and Heiko Paeth's group developed a novel machine learning model to improve climate model precipitation estimates which we will present at the European Geosciences Union's (EGU's) General Assembly 2021 in a PICO presentation.

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Lectures

Our lectures and seminars cover fundamental topics like databases and algorithms as well as more specific methods like natural language processing, machine learning, information retrieval.

An overview can be found here.

Theses and Practica

We offer various topics for theses and practica on all our research topics. As a BA/MA student you will have access to the CAIDAS cluster to do your research.

Find your thesis topic here!

Job Offerings

We're always looking for help, whether with research related topics, teaching or administration and offer work for variable amounts of hours. You'll also gain access to the CAIDAS cluster for your work.

For more information, check out our job offers!