My research interests involve developing model-driven approaches for understanding and analyzing interactions in Internet of Things (IoT) systems. I explore how formal methods and process mining techniques can be combined to represent IoT behaviors and support the automated generation and assessment of interaction models.

A key focus of my research is investigating how interaction models can be derived from different stages of the IoT system lifecycle, including design-time configurations such as smart home automation rules and runtime observations such as execution logs collected from IoT devices. These models are then analyzed using techniques such as conformance checking and model checking to examine system behaviors and identify inconsistencies or potential issues arising from deterministic, uncertain, and concurrent interactions.

My research is currently applied to smart home and smart lighting environments, with the aim of improving the reliability and understanding of interactions in increasingly complex IoT systems.