Yuting Fu
Papers
1
Total Citations
17
H-Index
1
About
Yuting Fu is a leading researcher in the safety validation of autonomous vehicles, with a primary focus on fault injection methodologies for in-vehicle electronics. Her most-cited work, "A Retargetable Fault Injection Framework for Safety Validation of Autonomous Vehicles" (2019, 17 citations), directly addresses the critical challenge of testing complex software in Electronic Control Units (ECUs) as mandated by the ISO 26262 functional safety standard. Fu’s major contribution lies in developing a retargetable framework that enables systematic fault injection during both component and system-level design phases, allowing engineers to simulate and assess the impact of hardware and software faults on vehicle safety. This work is particularly notable for its practical applicability, bridging the gap between theoretical safety standards and real-world validation. By providing a structured approach to uncovering vulnerabilities in autonomous driving systems, Fu’s research has become a foundational reference for engineers and researchers working to ensure the reliability of next-generation vehicles. Her framework not only enhances safety assurance but also accelerates the development cycle by enabling early fault detection, making her a key contributor to the field of dependable autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1