Tianyang Wang

Tianyang Wang's work centers on diagnosing faults in rotating machinery (such as bearings and gears) and monitoring the health of mechanical systems like wind turbines, using signal processing methods (like time-frequency analysis) combined with machine learning and deep learning techniques. The publication record also includes some titles in unrelated areas such as medical imaging, immunotherapy, and food chemistry, suggesting either broad collaborations or a shared name across multiple researchers. Prospective students interested in machinery fault diagnosis, structural health monitoring, and applying AI methods (attention networks, diffusion models, transformers) to engineering diagnostics would find the core research most relevant.

Publication output has grown substantially over the last decade, with a marked increase from roughly 20 papers per year in 2021-2023 to 60+ in 2024 and 2025.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026