Assistant Professor

Renata Medeiros de Carvalho

Department / Institute
Mathematics and Computer Science
Group
Process Science
EAISI Foundational
EAISI Health

RESEARCH PROFILE

Renata Medeiros de Carvalho is an Assistant Professor at Eindhoven University of Technology (TU/e). Her research interests are focused on, but not limited to, adaptive and declarative business processes and Business Process Management (BPM). She works in the domain of flexible business processes in particular, and how this can enrich business process models with domain-specific knowledge. 

BPM and BPM systems have only solved the ’easy problems’: 1) business processes where a handful of contingencies handle all situations, and 2) processes where most of the activities can be automated. However, knowledge intensive processes do not lend themselves to such rigid formalizations: both the set of activities to perform, and the content of each activity, depend heavily on a combination of domain-specific knowledge, and the case at hand. Renata is interested in both pragmatic issues of modeling convenience and how flexibility is represented and/or can be detected through recorded data. She is currently conducting research into Object-Centric Behavioral Constraint (OCBC) modeling language, which combines ideas from declarative, constraint-based languages such as Declare, and from data/object modeling techniques (ER, UML, or ORM). 

ACADEMIC BACKGROUND

Renata Medeiros de Carvalho received her PhD in Computer Science from the Center of Informatics (CIn), Federal University of Pernambuco (UFPE), Brazil in 2015. She also holds an MSc an BSc in Computer Engineering from the University of Pernambuco (UPE), Brazil. She has also worked as a postdoctoral researcher at LATECE - Laboratory for Research on Technology for Ecommerce in the University of Quebec at Montreal (UQAM).  

She publishes regularly and has been awarded a Xerox University Affairs Committee Grant and NSERC Engage Grant. Renate is also local coordinator of two Master programs: EIT Digital Data Science and Erasmus Mundus Big Data Management and Analytics (BDMA).