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.

This study presents a machine learning framework for predicting the Young's Modulus (YM) of biomedical titanium alloys to address stress shielding in implant applications. A Deep Neural Network (DNN) was developed using nineteen compositional features and physically meaningful descriptors. Prior to model training, the...

Muhammad Shahmir Saif, Muhammad Ali Siddiqui, Fahim Raees · Scientific Reports · 0 citations

Open access Jul 2026

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

We present a systematic ablation study of physics-informed neural networks (PINNs) for level-set advection across four benchmarks of increasing complexity: linear translation (TR), solid-body rotation (RO), reversed vortex deformation (RV), and the Zalesak rotating slotted disc (ZD), covering 69 experiments. For TR, a...

Muhammad Akbar Khan, Fahim Raees · Machine Learning: Science an... · 1 citation