The topics include but are not limited to:

• Implementations of Machine learning (ML) in development of advanced metrology tools, including:

- Machine vision and smart computational imaging

- Interferometric optical metrology

- Scanning probe microscopy (SPM)

- Scanning electron microscopy (SEM)

- Optical scatterometry

- Hybrid metrology and data fusion

- Data augmentation in Precision and Micro/Nano Metrology (PMNM) using ML

- Calibration of sensors and measuring instruments

- Optical sensors and instrumentation

- Non-optical sensors and instrumentation

- Other emerging and innovative measuring techniques

• Applications of ML in innovative and emerging industries, including:

- Precision surface texture analysis for condition monitoring and fault diagnosis

- Micro-defects identification or classification using ML methods

- Metrology and inspection in semiconductor industry

- Enhancing modeling for measurement techniques and/or uncertainty analysis

• Remaining open issues of ML in PMNM

- Advanced ML techniques

- Explainable and Trustworthy ML in PMNM