ECDA is an international conference with the main focus on data science and data mining which is being held in different European cities since 2013 almost every year. This year the conference was held in Paderborn, Germany. This 3-days conference hosted many interesting keynotes and a large number of talks given by scientists from all over the world. Prof. Wolfgang Konen organized and chaired the "Time Series Analysis and Online Algorithms"  session. In the same session Markus Thill presented his recent work "Online Adaptable Time Series Anomaly Detection with Discrete Wavelet Transforms and Multivariate Gaussian Distributions" and he received valuable remarks and feedback. The deadline for the paper  submission is on 15th of September and after successfully passing through a reviewing process the work will be published in Archives of Data Science, Series A Journal.

Digital Xchange Conference was held on 23rd of July in TH Köln, Campus Gummersbach as a collaborative work of Opitz consulting company and TH Köln. The event attracted over 600 audience and the talks covered a large area of digitalization field including cloud computing, artifical intelligence, industry 4.0, augemented reality, IT security and many more interesting topics. 

"Machine Learning and AI for Predictive Maintenance" is the title of an interesting presentation given by our research team member Mr. Markus Thill. Markus Thill presented an overview of his PhD research topic which he is pursuing at TH Köln under the supervision of Prof. Wolfgang Konen. He discussed several anomaly detection algorithms and their performances. The talk attracted a lot of attention from the audience.

The R package TDMR (Tuned Data Mining in R) is now available on CRAN in a major new release 2.0. It supports the new R  package SPOT 2.0 (Sequential Parameter Optimization Toolbox) with its largely redesigned and simplified interface. TDMR 2.0 has as well a simplified interface. TDMR documentation and TDMR tutorials have been rewritten to account for the simpler interface.

Tuned Data Mining in R ('TDMR') performs the complete tuning of a data mining task (predictive analytics, that is classification and regression). Preprocessing parameters and modeling parameters can be tuned simultaneously. It incorporates a variety of tuners (among them 'SPOT' and CMA with package 'rCMA') and allows integration of additional tuners. Noise handling in the data mining optimization process is supported, see Koch et al. (2015) <doi:10.1016/j.asoc.2015.01.005>.

More information on TDMR is available on the TDMR project page.

GBG (General Board Game Playing & Learning) is an Open Source software framework developed at TH Köln, University of Applied Sciences. GBG aims to ease the entry for the students in Game learning research area which is a very interesting sub-field of artifical intelligence. Last year, two students finished their Bachelor theses successfully on the basis of the GBG under supervision of Wolfgang Konen

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The annual Computational Intelligence workshop in Dortmund is a great place for sharing new ideas and recent work done in computational-intelligence related topics. This year, the GMA workshop took place on 23-24 of November at the Dorint Hotel in Dortmund. Our team presented two papers in the fields of surrogate models and time series analysis. In total there were 4 papers presented from members of TH Köln, Campus Gummersbach.

Besides receiving effective feedbacks about our own work, we also had a chance of  listening to many interesting talks about related research work, done in different universities. The presentations had very diverse topics: from more practical ones to very abstract and mathematical ones. The friendly atmosphere, constructive critics and open discussions make this workshop very special and productive.