Dr. Chiara Di Francescomarino 

Date/Time: 11.04.2018, 15:00 

Location: D2.3.103 

Abstract 

Predictive process monitoring aims at predicting the future of an ongoing process execution by learning from past historical business process executions. Different approaches have been proposed in the literature in order to provide predictions on the outcome, the remaining time, the required resources as well as the remaining activities of an ongoing execution, by leveraging information related to the control flow, the data flow, or even unstructured text contained in event logs, recoding information about process executions. The approaches can be of different nature and, some of them also equipped to offer users support in tasks such as parameter selection. This talk will provide an overview of some of the approaches and the research directions characterizing the field of predictive process monitoring.

Bio 

Chiara Di Francescomarino is a researcher at Fondazione Bruno Kessler (FBK) in the Process and Data Intelligence (PDI) Unit. She received her PhD in Information and Communication Technologies at FBK and University of Trento, Italy, in 2011 by mainly investigating topics related to the semantic annotation of business processes and the automated reasoning capabilities that semantic annotations can provide. She is currently working in the field of business process management, by extending her research interest from business process modeling to process execution. Specifically, she is currently investigating problems related to process monitoring (e.g., in situations of incomplete execution traces), process repair (given execution traces non-compliant with the model), discovery of hybrid (formal and informal) process models, as well as predictive process monitoring based on historical execution traces.