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Data Science Chair

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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.

Contact:

EMail:     sekretariat.lsx[at]uni-wuerzburg.de
Phone:   (+49 931)  31 - 89675
Fax:        (+49 931)  31 - 86732

Address:  Chair of Data Science (Informatik X)
                  Am Hubland
                  97074 Würzburg

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Publications
Theses / Practica
Teaching

News

Best ML Innovation Award for "Deep Learning for Climate Model Output Statistics"

Our group together with Heiko Paeth's group developed a novel machine learning model to improve climate model precipitation estimates for which we have received the Best ML Innovation Award on the Tackling Climate Change with Machine Learning Workshop at NeurIPS 2020.

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New interactive Climate Atlas of Lower Franconia for the BigData@Geo website

The interactive web portal of the BigData@Geo project has been available since October 2018. After consultation with the cooperating small and medium-sized enterprises (SME), the portal has now been fundamentally revised.

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LM4KG

Our paper "LM4KG: Improving Common Sense Knowledge Graphs with Language Models" has been presented at ISWC 2020

Our paper "LM4KG: Improving Common Sense Knowledge Graphs with Language Models" concerning the enrichment of knowledge graphs through a pre-trained language model was presented at the International Semantic Web Conference (ISWC) 2020.

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Music & AI Project "Mozart Genom" at Wuerzburg Web Week (Update)

Our Music & AI Project was presented within the section "Mozart & KI" at Wuerzburg Web Week.

This teaching project wants to explore the ability of Artificial Intelligence and Machine Learning to understand the fundamental creative ideas of music and composition and is part of the Mozartfest initiative Mozart & KI.

 

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For students:

We offer interesting student jobs in different categories (see below) ranging from short to long periods. For a complete list of latest jobs, please visit our wiki. For questions please contact Tobias Koopmann. 

Admin

We run our own Kubernetes Cluster in order to run all our applications and research. In this area, we can offer a lot of tasks for enthusiastic students. 

Organisational & Teaching

We offer different organisational and/or teaching tasks, starting for example with administering our web appearance to several teaching tasks regarding out lectures. 

Programming

Since we are a computer science chair, most of our student tasks are programming-related. They distinguish in development tasks (e.g. website development) or research tasks (e.g. implementing neural network baselines for our current research).  

For Phd students:

Currently we offer no open Phd student jobs.