Dr. Julien Siebert

Julien Siebert is working as a researcher in the Data Science department of Fraunhofer IESE. He studied Artificial Intelligence and Engineering Science and got his PhD in Computer Science. His professional interests include data science processes, neural networks, complex systems, and non-linear modeling.

What are Complex Systems? – Understanding and Assessing Complex Phenomena

Taking into account the complexity of the systems around us is the first step towards understanding them. In this post, our expert Dr. Julien Siebert (Fraunhofer IESE) describes the most important characteristics of complex systems from his point of view….

Time Series Analysis: Pattern Recognition

Time Traveling with Data Science: Pattern Recognition, Motifs Discovery and the Matrix Profile (Part 4)

In Part 4 of our Fraunhofer IESE blog series on „Time Traveling with Data Science“, we continue our journey in the field of time series analysis. In this blog post, our experts from Fraunhofer IESE and our guest author Markus…

Agile Machine-Learning-Prozesse für KMU

Agile Machine Learning-Prozesse für KMU

Agile Machine Learning-Prozesse können für kleine und mittelständische Unternehmen (KMU) ein wahrer Erfolgsfaktor sein: Agile Praktiken haben sich als großer Vorteil bei der Entwicklung von Software-Systemen bewährt. Mit dem Wandel zu datengetriebenen Produkten und Dienstleistungen müssen nun jedoch diese Software-Entwicklungsprozesse…

Time Series Analysis: Outlier Detection

Time Traveling with Data Science: Outlier Detection (Part 3)

In our blog series on „Time Traveling with Data Science“, we previously introduced different tasks in time series analysis. In this blog post, we now present the task of Outlier Detection. Outliers are data so different from others that one…

Scope Compliance

Scope Compliance – Die Rolle des Anwendungskontexts im Machine Learning

Im Rahmen unserer Blogreihe »Scope Compliance« beschäftigen wir uns mit der Bedeutung des Anwendungskontexts im Machine Learning. Im ersten Beitrag klären wir ein häufig anzutreffendes Missverständnis auf und arbeiten seine Implikationen für die Praxis heraus. Sie erfahren, warum es entscheidend…

Time Series Analysis (Change Point Detection)

Time Traveling with Data Science: Focusing on Change Point Detection in Time Series Analysis (Part 2)

In the first blog post of our „Time traveling with data science“ series, we presented several tasks related to the analysis of time series. In this post, we dive into the task called „change point detection“.   Changes in time series or…

Time traveling with data science: Focusing on time series analysis

Time Traveling with Data Science: Focusing on Time Series Analysis (Part 1)

Time traveling with data science: In this blog series, we will cover some of the different techniques that make up time series analysis. This first post will provide an overview of the different types of analysis possible and answer the…

What does Paul Bocuse (French three-star-decorated chef) have to do with Data Science?

You wonder how a Data Scientist works? The data science process (i.e., building data-driven products such as recommendations systems, fraud detection systems, chatbots, etc.) is, in some sense, similar to what a chef like Paul Bocuse in a restaurant does…

Was hat der Drei-Sterne-Koch Paul Bocuse mit Data Science zu tun?

Der Data-Science-Prozess (d.h., die Erstellung datengetriebener Produkte wie Empfehlungssysteme, Betrugserkennungssysteme, Chatbots etc.) ist in gewissem Sinne dem ähnlich, was ein Koch in einem Restaurant bei der Vorbereitung eines neuen Menüs macht. Er muss etwas neues kreieren, das die Gäste anspricht,…