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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

Our paper "Towards Explainable Occupational Fraud Detection" has been accepted at MIDAS 2022

In our paper, we investigate the performance and interpretability of machine learning approaches when detecting occupational fraud in company data, finding models that give both strong performance and comprehensible decisions.

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Our paper "NeuralPDE: Modelling Dynamical Systems from Data" has been accepted at KI2022

In our paper we use the Method of Lines together with Neural ODEs to learn spatio-temporal data arising from dynamical systems. We show that the method performs consistently well on a wide range of applications.

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We provide public ERP system data for automated fraud detection

We've created an approach for constructing synthetic ERP system data with different cases of occupational fraud to help researchers develop automated detection approaches.

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Our paper "Semi-unsupervised Learning forTime Series Classification" got accepted @ MILETS (KDD22)

Our workshop paper "Semi-unsupervised Learning forTime Series Classification" got accepted @ MILETS (8th SIGKDD International Workshop on Mining and Learning from Time Series -- Deep Forecasting: Models, Interpretability, and Applications) at KDD22.

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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!