Álvaro Valencia-Parra obtained his B.S degree in Software Engineering at the University of Seville in 2017. In 2019, he graduated with honors from the University of Seville with a M.Sc. degree in Computer Engineering. Currently, he is a PhD student. His research areas include the improvement of different activities in the Big Data Pipeline, such as data transformation, data quality, and data analysis. The scenarios he is facing up are mainly focused on the process mining paradigm. Hence, his goal is to improve the way in which final users deal with data preparation and specific scenarios in which configuring a Big Data Pipeline might be tricky. For this purpose, he is working in the improvement of these processes by designing Domain-Specific Languages, user interfaces, and semi-automatic approaches in order to assist users in these tasks. He has participated in prestigious congresses such as the BPM Industry Forum or the International Conference on Information Systems (ICIS).

Education

• PhD Student in Computer and Software Engineering in the University of Seville. Title: “Improving Big Data Pipelins to Assist Organisations in the Automation of Business Processes“. Supervisors: María Teresa Gómez-López and Ángel Jesús Varela-Vaca.
• MSc degree (2019) in Computer and Software Engineering degree from the University of Seville. Master thesis: “Big Data Pipelines: Challenges and Opportunities“. Supervisors: María Teresa Gómez-López and Ángel Jesús Varela-Vaca.
• BSc degree (2017) in Software Engineering from the University of Seville. Thesis: “Analysis and integration of Big Data tools with modern web information systems“. Supervisor: Inmaculada Hernández Salmerón.

Research Areas

• Analysis and optimisation of Big Data Pipelines.
• Design of Domain-Specific Languages for supporting data preparation
• Automation of the Data Quality process in Big Data Pipelines.
• Big Data Architectures
• Conformance Checking

Research Profiles

ResearchGate

Google Scholar

DBLP

Orcid