Dr. Yang Song | Fault Diagnosis | Research Excellence Award

Dr. Yang Song is a researcher in intelligent systems and control engineering, specializing in fault diagnosis, data-driven methods, and reliability analysis for complex dynamic systems. Her work focuses on parity space techniques, machine learning integration, and advanced fault detection and isolation strategies applied to engineering systems such as gas regulators and autonomous technologies. She has contributed significantly to both theoretical advancements and practical implementations in control systems and automation. Her scholarly impact is reflected in Scopus metrics with 247 citations across 15 documents and an h-index of 5, alongside growing recognition on Google Scholar through increasing citations and research visibility in intelligent fault diagnosis and control engineering domains.