Daniel Quinn

Assistant Professor

Contact
MEC 310
351 McCormick Road
PO Box 400743
Charlottesville, VA 22904-1000

Phone: (434) 924-9576
FAX: (434) 924-8818
Email: danquinn@virginia.edu

Research
Professor Quinn’s research group studies how fluid dynamics can improve cyber-physical systems like autonomous vehicles and energy harvesters. In the realm of autonomous vehicles, Quinn’s group explores how advanced aerial and underwater robots can make use of predictive fluid models. These models are especially important in conditions where traditional data-driven controllers are unstable, such as when traveling in swarms, near solid boundaries, in crossflows, or in heavy turbulence. Special attention is paid to bio-inspired robotics, so experiments are designed to not only improve vehicle control, but also to provide insights into biolocomotion. The second branch of Quinn’s group studies how fluid models can enable next-generation flow sensors and energy harvesters. Specifically, his group explores how future sensors/harvesters can improve efficiency by combining fluid dynamics, network dynamics, and machine learning. As with autonomous vehicles, experiments are designed to share insights with biologists, in this case by drawing analogies with sensors and energy recapture strategies found in nature.