My research is at the intersection of fluid mechanics and data-science. Specifically, my graduate research focused 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. Experimentally controlling, optimizing, and visualizing array dynamics was at the core of this work. I also studied 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. My postdoctoral research is utilizing frequency-domain methods and data assimilation to augment turbulence modeling.

Postdoctoral Scholar in Mechanical & Civil Engineering, Caltech (current)

(Supervisor: Tim Colonius)

Ph.D. in Mechanical Engineering, University of Washington 2022

(Advisors: Steve Brunton & Brian Polagye)

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

Sc.B. in Mechanical Engineering, Brown University 2017

email: ischerl at caltech dot edu