Rober MamaniRober Mamani
Atmospheric modeller & Data scientist
I am a researcher and engineer specializing in wind energy, air quality, and environmental modelling. My work integrates computational fluid dynamics, numerical simulations, and data-driven analysis to understand, predict, and optimize complex atmospheric systems, using tools such as WRF, CHIMERE, and OpenFOAM alongside Python for data processing and analysis.
I hold a PhD in Wind Energy from the Université Libre de Bruxelles (ULB), Belgium, where my doctoral research focused on assessing wind energy potential over complex terrain at the mesoscale in the Bolivian Andes. Using the Weather Research and Forecasting (WRF) model, I studied how high-altitude conditions, lake-driven circulation, and complex topography shape wind resource availability, combining these simulations with reanalysis data to evaluate wind energy potential across different regions and altitudes of Bolivia.
Beyond wind resource assessment, I have worked on CFD modelling with OpenFOAM to examine flow behaviour in complex and urban environments, and applied atmospheric chemistry modelling with CHIMERE to study air quality dynamics. My more recent work brings these threads together in high-resolution urban-scale studies, integrating wind flow, ventilation, heat stress, and air quality analysis, as well as multi-scale assessments combining wind and solar energy potential with infrastructure considerations.
