Luigi Galasso
Papers
2
Total Citations
12
H-Index
2
About
Luigi Galasso is a researcher focused on the critical intersection of hardware reliability and artificial intelligence, specifically investigating the vulnerability of neural networks deployed on Graphics Processing Units (GPUs). His primary research areas include fault tolerance, hardware reliability assessment, and the dependability of deep learning accelerators. Galasso’s major contribution lies in developing systematic frameworks to evaluate how permanent hardware faults—such as those caused by manufacturing defects or aging—impact the accuracy and safety of Convolutional Neural Networks (CNNs) and Deep Neural Networks (DNNs). His influential work, including the highly cited paper "Reliability Assessment of Neural Networks in GPUs: A Framework For Permanent Faults Injections" (2022, 7 citations), provides essential methodologies for injecting faults and measuring their effects, a crucial step for deploying AI in safety-critical domains like autonomous driving, robotics, and healthcare. Complementing this, his study "Evaluating the impact of Permanent Faults in a GPU running a Deep Neural Network" (2022, 5 citations) offers empirical insights into the real-world consequences of such hardware failures. By bridging the gap between hardware reliability and AI performance, Galasso’s research is foundational for engineers and scientists working to ensure that next-generation intelligent systems are both powerful and trustworthy.
Research Focus
Key Achievements
Top Papers
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- 2