Workshop

Are you interested in the topic of »Anomaly Detection,« or are you already working in the field and looking for an opportunity to present your work or engage in exchange and discussion? If so, this workshop is just right for you!

Our department »Financial Mathematics« is hosting a workshop on anomaly detection in collaboration with the »Smart Data and Knowledge Services« research group at the German Research Center for Artificial Intelligence (DFKI)).

The focus – besides an introductory talk for those interested – is on your research into the latest developments in anomaly detection and its applications in industry. The goal of the workshop is to provide space for academic research and practical experience, spark engaging discussions during coffee breaks, and create opportunities for networking.

Researchers, students, developers, and experts from both industry and academia who are interested in data-driven and AI-supported methods for anomaly detection are invited. Prior knowledge in data analysis or machine learning (ML) is helpful but not a requirement.

For example, the following focus areas are part of the research field and would welcome presenters:

• Detecting anomalies, outliers, and novelties
• Sampling outside the distribution
• Detecting change points in time series
• Using AI to explain existing anomalies
• Utilizing federated learning to compare anomalies across different separate datasets
   

Focus Topics in the Workshop Program

The workshop consists of two half-days that we want to fill together with you. The first half-day will focus on the academic world. There will be room for your research. The second half-day will shift the focus to practice. Practitioners from industry are warmly invited to share where anomaly detection is applied in their companies or where finding anomalies is still seeking a solution. We will also report on projects we have conducted in collaboration with industry to demonstrate the practical relevance of anomaly detection.

In our workshop, we will jointly explore how to recognize, interpret, and effectively utilize anomalies. The hope is that this raises open questions and new research directions – an ideal foundation for exchange, networking, and future interdisciplinary collaboration.