Luca Berardinelli

Registered user since Tue 7 Jul 2020

Name: Luca Berardinelli

Bio: Dr. Luca Berardinelli (male) is a postdoctoral researcher. He received his PhD degree (2011) from University of L’Aquila in Italy. Postdoctoral researcher at Department of Information Engineering Computer Science and Mathematics of the University of L’Aquila, Business Informatics (BIG) and Distributed System (DSG) groups at TU Wien and then at JKU Linz Department of Business Informatics – Software Engineering (BISE). During his research career he participated as representative of research institutions to national (CDL-Flex http://cdl.ifs.tuwien.ac.at/) and European FP7/H2020-funded projects (PLASTIC, VISION, PRESTO, CRAFTERS, U-TEST, all available on https://cordis.europa.eu/), working on MDE approaches applied to service-oriented and cyber-physical systems. Active researcher with experience in the private sector, he published more than 30 peer-reviewed publications and his interests include model-driven non-functional analyses, context and uncertainty modeling, DevOps, among many others. Currently, he is working on the model-driven engineering approaches for production systems (CDL-MINT, https://cdl-mint.se.jku.at) and combination of DevOps and MDE principles and practices (Lowcomote, lowcomote.eu).

Country: Austria

Affiliation: Johannes Kepler University Linz

Personal website: https://www.linkedin.com/in/lucaberardinelli/

Research interests: Model Driven Engineering, Low Code Platforms, DevOps, Uncertainty

Contributions

SEAMS 2021 Author of RoboMAX: Robotic Mission Adaptation eXemplars within the SEAMS 2021-track
MODELS 2020 Author of DevOpsML: Towards Modeling DevOps Processes and Platforms within the Posters-track
ISSTA 2020 Author of Uncertainty Modeling and Evaluation for Dependable IoT Cloud Systems Design within the TAV-CPS/IoT-track
ICSE 2020 Author of Dealing with Non-Functional Requirements in Model-Driven Development: A Survey within the Journal First-track
ISSTA 2017 Author of Testing Uncertainty of Cyber-physical Systems in IoT Cloud Infrastructures – Combining Model-Driven Engineering and Elastic Execution within the TECPS-track