In 2016 Dr. Grabocka graduated in Machine Learning from the University of Hildesheim with his dissertation titled "Invariant Features For Time-Series Classification", which was awarded the biannual prize as the best PhD thesis of the Faculty of Natural Sciences at the University of Hildesheim. He pursued a PostDoc role at the Information Systems and Machine Learning Lab, University of Hildesheim, between 2016 and 2019 during which he worked mainly on industrial cooperation research projects, such as the one with the Volkswagen Financial Services on smart parking, residual value forecasting and automatic vehicle damage assessment.
The primary research interest topics of Dr. Grabocka are the mining of large-scale spatio-temporal data, more particularily particular time-series classification. Recently, his focus has been on the automatic configuration of Machine Leearning algorithms that are deployed with minimal expert supervision.
Dr. Grabocka has published articles in selected Artificial Intelligence (AI) and Machine Learning (ML) venues, such as ACM SIGKDD, SDM, AAAI, DAMI, or IEEE TKDE. He is a regular program committee of AI and ML conferences, such as AAAI, IJCAI and ECML, as well as a reviewer for the jornals DAMI, IEEE TKDE, or MACH.