Mechanical Engineering Associate Professor Austin Downey was recently named recipient of the 2025 Gary Anderson Early Achievement Award. He received the award at the American Society of Mechanical Engineers Smart Materials, Adaptive Structures and Intelligent Systems (SMASIS) conference in St. Louis this past September.

Established in 2006, the award recognizes a rising researcher whose notable contributions and work has already had an impact in their field within adaptive structures and material systems.

"I’m honored and grateful to receive the Gary Anderson Early Achievement Award,” Downey says. “To me, it recognizes a team effort of students and collaborators who are tackling the hard problem of making intelligent controls work at the microsecond timescales for safety-critical systems."

Downey was nominated for the award by Mechanical Engineering Professor Lingyu Yu. In her nomination letter, she explained that Downey is pioneering the field of real-time control for systems that experience high-rate dynamic events. Examples of these systems include hypersonic vehicles, active blast mitigation and air-bag deployment systems. Through these systems, Downey is investigating fundamental challenges related to real-time machine learning and microsecond model updating.

To accomplish his research goals, Downey co-designs structural control and model updating techniques with the design of field programmable gate array (FPGA), which is a versatile integrated circuit that can be programmed or reprogrammed to perform various digital functions. FPGA overlays enable ultra-low-latency structural control. His work also involves developing resource-aware control schemes that optimize the use of computational resources available on embedded control systems.

Downey has received nearly $5 million in research funding since beginning his career in academia at the University of South Carolina in 2018. Several of his research projects have been funded and supported by the Air Force Office of Scientific Research, Air Force Research Lab and National Science Foundation. These projects have focused on research in ultra-low latency machine learning and adaptive control of structures in extreme dynamic environments.