He has worked on multiple research projects, being his fields of expertise the application of numerical modelling and Machine Learning-based models to different areas of Hydraulic and Environmental Engineering: “Water Distribution Systems: modelling, pressure management and leakage management”, “Dam Engineering: geometric design, thermo-mechanical modelling”, “Prediction of water quality parameters and optimization of advanced treatments” and “Air quality forecasting”.

He is currently working for CIMNE (since October 2015), in the department of “Machine Learning in Civil Engineering” where he is involved in research, technical development (programming) and proposal development at national and European level. He is author or co-author of 9 articles in scientific journals and a book chapter as well as 25 contributions to conference proceedings. He is the creator of the 'AULA ETSI UPM-CIMNE', through which he collaborates with UPM in research and development of R+D+i projects, direction of Master's Thesis and Doctoral Thesis and teaching of classes

Fernando Salazar received the Degree on Civil Engineering from the Technical University of Madrid in 2002, specializing in Hydraulics. He has worked in several dam and hydraulic projects, as well as in the development of emergency plans and hazard-potential classification of dams (being Mequinenza and Riba-Roja, in the Ebro river, among them). He is working for CIMNE since 2009, where he is the current Project Development Director.

He obtained his PhD at the UPC in 2017, qualified as Excellent Cum Laude. It focused on the application of machine learning techniques to dam monitoring data analysis. In this field, he was winner of an International Challenge organized by Verbund, the greatest hydropower company in Austria.

He has been involved in several research projects in the fields of hydraulics, dam engineering and dam safety. He is author or co-author of 15 papers in scientific journals, and around 50 contributions in conference proceedings.