My research field is process mining, a field about novel algorithms used to understand business processes and improve them. Process mining sits between data science, business process management and machine learning, using bits and pieces from each field to create new algorithms and novel improvements to past works.
In particular, my research investigates the scope of data sources that can be included when analysing processes and how to adapt process mining techniques to take advantage of exogenous data sources. By increasing the variety of data sources included, process behaviour can be linked to broader environmental effects or can be categorised at key decision points within a process. While including such data can be achieved through data pre-processing or various aggregation techniques, my research looks to create a connection between a process and its contextual environment, which is not a one-way transformation.
Likely contributions include: algorithms that focus on multi-perspective discovery or enhancement for processes, visualisations for process models which change under distinct process environments and frameworks to construct a two-way transformation between processes and exogenous data sources.