Narges Dastanpour Hosseinabadi

Introduced an integrated approach for structural damage detection across concrete, steel, and glass using advanced technologies such as LiDAR and thermal imaging. Highlighted cross-material interactions to enhance diagnostics and enable predictive maintenance.

Developed an NLP-based medical note simplifier that transforms complex clinical instructions into plain, child-level English. Applied prompt engineering with Flan-T5 transformer models to extract patient-relevant actions and rephrase them into clear to-do items. Built dual Flask and Tornado backends with a printable web interface.

Contributed to the implementation and optimization of FMVSS201u-related models, exploring different neural network architectures and pre-trained models.

Focused on enhancing model accuracy and investigating alternative coding strategies.

Designed and implemented a robot path planning system capable of detecting white and black surfaces.

Optimized the system to balance speed with the ability to navigate curves without leaving the track, minimizing fundamental errors along a three-meter path.