Savandi Kalukapuge is currently studying for a PhD in Information Systems at the Queensland University of Technology (QUT). She holds a BSc. (Honours) in Information Technology (specialising in Information Technology). She has expertise in database systems, object-oriented programming, web development, software quality assurance, data structures and algorithms, IT project management and agile practices. Savandi has previous experience working as a software quality assurance engineer and she is also a tutor and a research assistant at QUT. Savandi is a member of the BPM Research Group at QUT and is avid about business process-oriented data and data quality management. Her PhD research focus is on quality drifts in process event streams, which are dynamic in nature due to the streaming context, and she hopes to scrutinise the challenges that are associated with such an environment. By adopting the Design Science Research methodology, her goal is to develop the necessary formalisations, tools and techniques for real-time detection and reporting of quality drifts in process event streams by amalgaming both process mining and data stream mining concepts and theories. As a result, she seeks to identify and rectify process event data quality issues on-the-fly, without waiting for static event logs to be prepared and analysed. Her work would ultimately contribute a solution to detect quality drifts (deviations) and support the informed management of business process event streams (through causal explanations on detected quality drifts). Research Interests Process mining, Data quality management, Process event streams