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Author

Reyhan Hosavci

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Jul 2026

Physics-Informed Feature Engineering for Machine Learning Prediction of Tight Binding Parameters in III-V Semiconductors

This work predicts sp tight binding parameters for nine III-V binary compounds from experimentally accessible observables without first-principles input, indicating that physics-informed feature engineering supports accurate, interpretable parameter prediction in the small-data regime.

Reyhan Hosavci, D. Malkoç · 0 citations
Conference Jul 2026

Structured CT Imaging Artefact Assessment using Vision-Language Models

X-ray computed tomography (CT) is one of today’s most critical imaging modalities, with a wide range of applications spanning from medical diagnosis to industrial inspection. CT images can be severely affected by physically induced degradations such as low-dose noise and beam hardening, which compromise image quality a...

Reyhan Hosavci, Raziye Kübra Kumrular · 0 citations

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