Aaron Towne

Aaron Towne is an Assistant Professor in the Department of Mechanical Engineering at the University of Michigan's College of Engineering. His research focuses on developing physics-based and data-driven reduced-complexity models for understanding, predicting, and controlling turbulent fluid dynamical systems. Prior to joining the University of Michigan faculty, he was a Postdoctoral Fellow at Stanford University's Center for Turbulence Research.

Towne received his PhD and MS degrees from the California Institute of Technology and his BS from the University of Wisconsin-Madison. His educational background has provided a strong foundation for his work at the intersection of fluid dynamics, computational methods, and data science.

Towne's research interests span fluid mechanics, reduced-complexity modeling, data-driven modeling, flow control, and aeroacoustics. His group develops innovative methods for analyzing turbulent flows, with particular emphasis on resolvent analysis, spectral proper orthogonal decomposition, and space-time model reduction techniques. Their work addresses fundamental questions about coherent structures in turbulent flows while developing practical tools for flow estimation and control.

The publication record demonstrates a strong trend toward developing scalable computational methods for analyzing complex fluid systems, with particular focus on turbulent jets, airfoil wakes, and boundary layers. Recent work has increasingly integrated data-driven approaches with physics-based modeling, creating hybrid methods that leverage the strengths of both paradigms. The research spans from fundamental fluid mechanics to practical applications in aerospace engineering and aeroacoustics.

Towne has received numerous prestigious awards including the Air Force Office of Scientific Research Young Investigator Program (YIP) award in 2020, an NSF CAREER Award in 2023, and an Office of Naval Research YIP award in 2024. He has also received multiple best paper awards from the American Institute of Aeronautics and Astronautics (AIAA) and American Society of Mechanical Engineers (ASME).

Towne actively mentors a diverse group of graduate students, currently advising seven PhD candidates and pre-candidates along with two master's students. His research has been supported by multiple grants from federal agencies including the Air Force Office of Scientific Research, National Science Foundation, and Department of Defense. His group has developed several open-source software tools including RSVD-Δt, RSVD-LU, and various implementations of spectral proper orthogonal decomposition.

Towne leads a vibrant research group focused on turbulence modeling and control. The group maintains the AIAA Database for Reduced-Complexity Modeling, which provides publicly available flow data to support research in the fluid mechanics community. Their work bridges theoretical fluid dynamics with practical applications, particularly in the areas of jet noise reduction and flow control.