Yaoxuan Zhu

PhD Candidate, Intelligent manufacturing - intelligent machining system(metal cutting), online monitoring process (data-driven based), multi-sensor fusion, production data analysis - feature engineering, deep learning/machine learning

Publication

[1] Zhu Y, Osterlind T, Rashid A, Archenti A. Engineering Applications of Artificial Intelligence: Data-driven approaches for surface quality monitoring and prediction based on heterogeneous multi-channel signal fusion in hard part machining 2025;160. https://doi.org/10.1016/j.engappai.2025.111865.

[2] Zhu Y, Rashid A, Österlind T, Archenti A. Leveraging classifier-guidance diffusion model for improved surface roughness prediction through synthesized audible sound signal. Procedia CIRP 2025;134:789–94. https://doi.org/10.1016/j.procir.2025.02.207.

[3] Zhu Y, Rashid A, Österlind T, Archenti A. Surface quality prediction in-situ monitoring system: A deep transfer learning-based regression approach with audible signal. Manuf Lett 2024;41:1290–9. https://doi.org/10.1016/j.mfglet.2024.09.156.

[4] Zhu Y, Rashid A, Österlind T, Archenti A. EUspen 's 24th International Conference & Surface roughness monitoring and prediction based on audible sound signal with the comparison of statistical and automatic feature extraction methods in turning process 2024:10–3. Link.