PhD Student @ the University of Washington

My research is at the intersection of experimental fluid mechanics and data-science. Specifically, I focus on cross-flow turbine (i.e. vertical axis turbine) arrays. This work is motivated by using cross-flow turbines as a renewable energy solution in wind and marine current applications. Cross-flow turbines have periodic dynamics that can be harnessed in arrays to increase performance as compared to isolated turbines. Experimentally controlling, optimizing, and visualizing array dynamics is at the core of my work. I also study how machine learning and other data-driven methods, such as robust principal component analysis and dynamic mode decomposition, among others, can be applied in experimental fluid mechanics.

keywords: fluid mechanics, controls, optimization, dimensionality reduction, cross-flow turbines (vertical-axis)

M.S. in Mechanical Engineering, University of Washington 2019

Sc.B. in Mechanical Engineering, Brown University 2017

email: ischerl@uw.edu

Check out my new paper on robust modal decompositions for fluid flows! [paper] [video abstract]