Author

Fahim Raees

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Jul 2026

A Physics-Informed Neural Operator for Thermal Ranking of Low-Cost Wall Materials in Hot-Dry Climates

Identifying cost-effective indigenous building materials that minimise heat penetration through walls is critical for indoor thermal comfort in low-income rural housing in hot-dry climates, where summer temperatures routinely exceed 45 C. We present a two-stage computational framework for thermal ranking of five low-co...

Muhammad Akbar Khan, Fahim Raees, Ubaida Fatima · arXiv.org · 0 citations

Open access Jul 2026

Predicting the Young's Modulus of biomedical titanium alloys using machine learning: a data-driven approach.

Comparative analysis with XGBoost, Random Forest, Gradient Boosting, and Support Vector Machine confirmed the capability of the proposed DNN model for capturing complex behavior non-linear relationships in Ti-Alloys data.

Muhammad Shahmir Saif, Muhammad Ali Siddiqui, Fahim Raees · Scientific Reports · 1 citation

Open access Jul 2026

A systematic study of physics-informed neural networks for the level-set interface advection

A key finding is an RFF–eikonal joint design constraint: at low bandwidth, weak eikonal regularization distorts the signed-distance field and underperforms the tanh baseline, whereas higher bandwidth is compatible with moderate regularization and yields the global best result.

Muhammad Akbar Khan, Fahim Raees · Machine Learning: Science an... · 2 citations