Our paper titled “Partitioner Selection with EASE to Optimize Distributed Graph Processing” has been accepted at IEEE International Conference on Data Engineering (ICDE 2023). It explores the use of machine learning to automate the selection of the optimal graph partitioning algorithm for a given distributed graph processing problem.