New Perspectives in Science Education
Gabriel Ibarra-Berastegi
Institution: University of the Basque Country
Country: Spain
I was awarded my Degree in Engineering at Bilbao´s Faculty of Engineering. Five years later, in 1993, I obtained my PhD degree in Environmental Engineering.
Currently, I work as a teacher and researcher at the Department of NE & Fluid Mechanics in the University of the Basque Country and I also act as a coordinator of the activities of EOLO research group http://www.ehu.es/eolo. In the area of, generally speaking, environmental modelling, I have led several research projects in the field of geophysical fluids, renewable energies, air pollution and climate change. I have also taken part in educational and research projects on the fluid mechanics aspects of the biofiltration of waste gases.
In my research activities, I use a variety of machine learning algorithms along with CFD for fluid mechanics, meteorology and environmental engineering studies. After many years using a great variety of software, at this moment, for all my educational and research activities, I have eventually come to using only two major tools: SATURNE (in the frame of CAE Linux) for CFD purposes and R for virtually everything else. In some of my research areas, I have also conducted consultancy works for some public institutions. As a result of this work, I have published several research papers in peer-reviewed journals and in 2013, along with other researchers from our University, we were granted a patent.
In 2004 I became a fellow of the Wessex Institute of Technology (UK) as “a recognition for his outstanding work”.
My research work involves the application of techniques like analogues, random forests and neural networks for classification, downscaling, trend detection, climate analysis and short-term forecasting purposes. The target variables are two groups of geophysical fluids:
i) The variables involved in the atmospheric water cycle
ii) Fluids associated with renewable energy like wind, and more specifically ocean wave energy flux. This type of energy, like other renewable sources has the problem of intermittency which originates electricity-grid management problems. Being able to forecast with a reasonable accuracy the energy that waves will hold a few hours ahead, can contribute to address this problem.
I teach Fluid Mechanics, Ocean Energy and Water Management to engineers. In these last two subjects I have successfully incorporated the software R into the regular teaching activities.
Areas of expertise: Water supply, Fluid mechanics, Ocean Engineering. Higher education, e-learning
Currently, I work as a teacher and researcher at the Department of NE & Fluid Mechanics in the University of the Basque Country and I also act as a coordinator of the activities of EOLO research group http://www.ehu.es/eolo. In the area of, generally speaking, environmental modelling, I have led several research projects in the field of geophysical fluids, renewable energies, air pollution and climate change. I have also taken part in educational and research projects on the fluid mechanics aspects of the biofiltration of waste gases.
In my research activities, I use a variety of machine learning algorithms along with CFD for fluid mechanics, meteorology and environmental engineering studies. After many years using a great variety of software, at this moment, for all my educational and research activities, I have eventually come to using only two major tools: SATURNE (in the frame of CAE Linux) for CFD purposes and R for virtually everything else. In some of my research areas, I have also conducted consultancy works for some public institutions. As a result of this work, I have published several research papers in peer-reviewed journals and in 2013, along with other researchers from our University, we were granted a patent.
In 2004 I became a fellow of the Wessex Institute of Technology (UK) as “a recognition for his outstanding work”.
My research work involves the application of techniques like analogues, random forests and neural networks for classification, downscaling, trend detection, climate analysis and short-term forecasting purposes. The target variables are two groups of geophysical fluids:
i) The variables involved in the atmospheric water cycle
ii) Fluids associated with renewable energy like wind, and more specifically ocean wave energy flux. This type of energy, like other renewable sources has the problem of intermittency which originates electricity-grid management problems. Being able to forecast with a reasonable accuracy the energy that waves will hold a few hours ahead, can contribute to address this problem.
I teach Fluid Mechanics, Ocean Energy and Water Management to engineers. In these last two subjects I have successfully incorporated the software R into the regular teaching activities.
Areas of expertise: Water supply, Fluid mechanics, Ocean Engineering. Higher education, e-learning
