We welcome you to the website of the Chair of Data Engineering. Since 2022, our chair, headed by Prof. Dr. Maria Maleshkova, has been based in the School of Electrical Engineering at Helmut Schmidt University.
You can find more information about the professorship and our work on the following pages.
Latest News
What actually happens in our bodies when we feel afraid? | 11.08.2026
Our Data Engineering professorship explores this question together with the University of Siegen.
An open dataset “ARACHNE” on spider phobia was collected, combining physiological measurements, behavioral data, and subjective assessments of fear. Fear responses were studied both during encounters with real spiders and in virtual reality (learn more about the project Fear detection for arachnophobia, https://www.hsu-hh.de/dataeng/en/research/current-projects/fear-detection-for-arachnophobia/).
The goal is to better understand fear responses using data, thereby creating a foundation for further research and, in the long term, more individualized therapeutic approaches.
Find out more about how ARACHNE was developed and what insights can be gained from the dataset in the full article here.
Our Research on the International Stage: IEEE EMBC 2026 | 26.07.-30.07.2026
Our Data Engineering group presented two research projects at the 2026 IEEE Engineering in Medicine and Biology Conference in Toronto.
Vaibhav Gupta presented an approach that systematically imputes missing heart-rate data, thereby improving the prediction of hypoglycemia in people with diabetes (learn more about the project GapSense). Mustafa Masjedi introduced a machine-learning method that analyzes three-dimensional cardiac maps and the spatial context of individual measurement points. The method aims to identify areas responsible for life-threatening cardiac arrhythmias more precisely and improve catheter ablation planning (learn more about the project CARDIO MAP-AI).
We are delighted by the strong international interest and the valuable exchange with fellow researchers. Our next step is to further refine both approaches methodologically.
Read the full article here.
Detect Earlier, Act Sooner: How Can Hypoglycemia Be Predicted Early? | 17.07.2026
For patients with type 1 diabetes, even small changes in blood glucose levels can have serious consequences. Our Data Engineering professorship explores this question together with DiaData (as part of the DiaMant project) to make data-driven predictions more reliable.
To achieve this, CGM data from more than 2,500 patients from different studies were combined, standardized, and preprocessed. The resulting dataset enables a more comprehensive analysis of blood glucose patterns and the development of models for the early detection of hypoglycemia. Find out more about how DiaData was developed and the potential of data-driven models for more individualized diabetes care in the full article here.
Visit by Prof. Dr. Klaus Beckmann to the Chair of Data Engineering | 26.05.2026
We recently had the pleasure of welcoming Prof. Dr. Klaus Beckmann, President of Helmut Schmidt University/University of the Federal Armed Forces in Hamburg, to our department’s laboratories.
We presented our current research projects in the fields of data engineering, data science, and artificial intelligence. These included, among other things, VR-based training and therapy simulations, systems for health and fitness analysis, our maritime situational awareness room, the cybersecurity hacking lab, and our stress lab.
The visit provided a valuable opportunity to exchange ideas on current research, technological developments, and future opportunities for collaboration. We would like to extend our sincere thanks to Prof. Dr. Klaus Beckmann for his interest in our work and the stimulating discussions.