Vincenzo Gallo
Papers
1
Total Citations
13
H-Index
1
About
Vincenzo Gallo is a leading researcher at the intersection of artificial intelligence and measurement science, with a primary focus on uncertainty assessment in neural-network-based systems. His most cited work, the 2023 survey "A Survey on Uncertainty Assessment in ANN-Based Measurements" (13 citations), provides a critical framework for quantifying reliability in AI-driven measurements—a foundational challenge as neural networks permeate industrial and research applications. Gallo’s contributions address the pressing need to move beyond black-box AI by developing rigorous methods for evaluating prediction confidence, directly impacting fields from sensor data analysis to automated decision-making. His research bridges the gap between theoretical metrology and practical machine learning, offering engineers and scientists tools to trust AI outputs in high-stakes environments. By systematically cataloging approaches to uncertainty quantification, Gallo has established himself as a key voice in making AI more transparent and accountable. His work continues to shape how researchers design robust measurement systems, ensuring that as AI becomes ubiquitous, its results remain verifiable and reliable.
Research Focus
Key Achievements
Top Papers
- 1A Survey on Uncertainty Assessment in ANN-Based Measurements13 citations · 2023