Welcome to the Homepage of the Data Systems Research Group at University of Tartu.

Our group conducts research and teaching that covers various aspects on the data management field (e.g., structured data, semi-structured data, graph data streaming data) with an emphasis on scalability mechanisms that effectively tackle the modern applications requirements (e.g., IoT, Smart Cities, Blockchain, Health Informatics) on dealing with Big Data and performing efficient Big Data Analytics.

The aim of our group is to get engaged and contribute in building the next-generation of efficient, scalable and insightful data systems. We love to build useful systems. If you have the same interest, please contact us.

We invite you to browse our website and learn more about our research and activities.



We are currently looking for motivated postdoc, PhD students and master students in the areas of big data management and processing systems. If you are interested to join our group, send us your application including detailed CV and publications to sherif.sakr [at] ut.ee. Please use the title "Joining Data Systems Groups @ UT" for your email message.


Our paper "A Decision Support Framework for AutoML Systems: A Meta-Learning Approach" has been accepted in the 1st IEEE ICDM Workshop on Autonomous Machine Learning (AML 2019)


Our paper "On the Interpretability of Machine Learning-Based Model for Predicting Hypertension" has been accepted in the BMC Medical Informatics and Decision Making Journal


Our paper "D2IA: Stream Analytics on User-Defined Event Intervals" authored by Ahmed Awad, Riccardo Tommasini, Mahmoud Kamel, Emanuele Della Valle, Sherif Sakr has been awarded CAiSE'19 best paper award. Congratulations Team!