Alex Rybchuk

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Alex Rybchuk’s research seeks to improve our understanding of the lower atmosphere, especially as it pertains to wind turbines. His current work centers on the RAAW field campaign, in which he seeks to bridge the gap between turbine inflow observations and simulations through the use of machine learning and traditional data assimilation techniques. In the past, he has conducted weather-scale analysis, conducting wind resource assessments off the coast of California and simulating wind plant wakes in the mid-Atlantic. 

Research Interests

Computational Fluid Dynamics

Boundary Layer Meteorology

Data Assimilation

Machine Learning

Model Validation, Verification, and Uncertainty Quantification

Education/Academic Qualification

Bachelor, Mechanical Engineering, Cooper Union for the Advancement of Science and Art

Master, M.S., Mechanical Engineering, University of Colorado Boulder

PhD, Mechanical Engineering, University of Colorado Boulder


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Collaborations and Top Research Areas From the Past 5 Years

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