Daniel Rodriguez Rey
About Daniel Rodriguez Rey
Daniel Rodriguez Rey is a post-doctoral researcher at the Barcelona Supercomputing Center, specializing in environmental engineering and air quality forecasting. He developed a traffic emissions model for his Ph.D. and is interested in applying machine learning to prediction models.
Work at Barcelona Supercomputing Center
Daniel Rodriguez Rey currently holds the position of Post-doctoral Researcher at the Barcelona Supercomputing Center, a role he has occupied since 2022. His work focuses on applying machine learning techniques to enhance prediction models, particularly in the context of urban air quality forecasting. Prior to this, he completed his Ph.D. at the same institution from 2017 to 2022, where he developed a model to estimate traffic emissions in Barcelona.
Education and Expertise
Daniel Rodriguez Rey has a strong educational background in Environmental Engineering. He earned his Ph.D. from Universitat Politècnica de Catalunya, where he studied from 2017 to 2022. He also holds an MSc in Air Pollution Management and Control from the University of Birmingham, completed in 2016. His undergraduate studies include a Master of Engineering in Chemical Engineering from Universitat Politècnica de Catalunya, which he completed in 2015. He has also participated in a student exchange program at the University of Ljubljana.
Background
Daniel has diverse professional experience in environmental consulting and research. He served as an Air Quality Consultant at Barcelona Regional in 2014 for five months. In 2016, he worked as a Field Monitoring Technician at enitial for six months. Additionally, he was involved with the Board of European Students of Technology as Vice-president of Public Relations from 2012 to 2013 in Barcelona, where he contributed to enhancing communication strategies.
Achievements
During his Ph.D. studies, Daniel developed a significant model for estimating traffic emissions in Barcelona, which contributes to understanding urban air quality dynamics. He is also involved in the development of CALIOPE-Urban, an urban air quality forecast system, and supports its adaptation for operational use in Barcelona's air quality forecasting. His skills in R and Python facilitate his work in data science and data mining applications.