David Oygenblik

David Oygenblik is a graduating Ph.D. candidate at the Georgia Institute of Technology in the Cyber Forensics Innovation Lab. His research spans AI systems and systems security, with a focus on making AI deployed on robots and edge devices more efficient, adaptive, and reliable. His work combines program analysis and memory forensics for understanding AI failures with elastic inference that adapts model capacity to changing computational resources and real-time deadlines. He is a recipient of the DOE Office of Science Graduate Student Research Award and the GTRI Graduate Student Fellowship, and currently conducts research at the National Lab of the Rockies.